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1、1LIBERIA GROWTH DIAGNOSTIC STUDYBY THE AFRICAN DEVELOPMENT BANK34African Development Bank GroupAbidjan 01,Cote dIvoirePhone(standard):+225 2720263900Internet:www.afdb.org.This paper is a product of the Economic Governance and Knowledge Management Vice Presidency(ECVP),African Development Bank.It is
2、a part of a larger effort by the African Development Bank to provide open access to its research and contribute to development policy discussions around the world.ECVP policy papers are also posted on the web at https:/www.afdb.orgThe paper series disseminate the findings of work in progress to enco
3、urage the exchange of ideas about development issues.An objective of the series is to get findings out quickly.The papers carry the names of the authors and should be cited accordingly.The findings,interpretations,and conclusions expressed in these papers are entirely those of the authors.They do no
4、t necessarily represent the views of the African Development Bank and its affiliated organizations,or those of the Executive Directors of the African Development Bank or the governments they represent.Rights and PermissionsThe material in this publication is subject to copyright.Because the African
5、Development Bank Group encourages dissemination of its knowledge,this publication may be reproduced,in whole or in part,for non-commercial purposes as long as it is fully attributed to this publication.Please cite the work as follows:Economic Governance and Knowledge Management Vice Presidency(ECVP)
6、.2023.Liberia Growth Diagnostic Study.African Development Bank.Abidjan,Cote dIvoire.Abbreviations and acronymsForewordAcknowledgementsExecutive SummaryIntroduction1.2 Binding Constraints of Growth from Growth Diagnostic studies of LiberiaChapter II:Return to Factor Accumulation:Macroeconomic and Sec
7、toral Level Growth Diagnostics2.1.The Supply Side:Factor Accumulation and Growth 2.2 Sectoral Source of Growth,Productivity and Structural Change2.3 The Demand Side Sources of Growth2.4 Summary:Hierarchy of the Binding Constraints at the Macro and Sectoral LevelsChapter III:Low Private Appropriabili
8、ty:Low Private Return to Economic Activity3.1 Low Social Return and Law Private AppropriabilityChapter IV:Macro and Micro Level Risk-Government and Market Failures and Low Private Appropriability4.1 Macroeconomic and External Sector Risks4.2 Microeconomic Risks789340475152646469Chapter V:
9、High Cost of Finance and Low Private Appropriability5.1 Domestic Finance5.2 External FinanceChapter VI:Public Appropriability:Building a Stable and Cohesive Society with Durable Peace6.1 Introduction:Modifying the GD Approach6.2 Political Stability and Good Governance for Growth6.3 Poverty Reduction
10、 through Inclusive Growth for Durable PeaceVII.ConclusionReferencesAppendices7373768957Abbreviations and acronymsABBREVIATIONS AND ACRONYMSAfCFTAAfrican Continental Free Trade AgreementAfDBAfrican Development BankBOPBalance of PaymentsCBLCentral Bank of LiberiaCPIACountry Policy and Insti
11、tutional AssessmentsECOWASEconomic Commission of West African States FDIForeign Direct InvestmentICORIncremental-Capital-Output RatioIMFInternational Monetary FundODAOverseas Development AssistanceODIOverseas Development InflowsGDGrowth DiagnosticGDPGross Domestic ProductGNIGross National IncomeHDIH
12、uman Development IndexMRIMarginal Returns on InvestmentNPLNon-Performing LoanPPPPublic Private PartnershipsSMEsSmall and Medium EnterprisesTFPTotal Factor ProductivityTOTTerms of TradeTVETTechnical and Vocational Education and TrainingUAEUnited Arab EmirateUNUnited NationsUNCTADUnited Nations Commis
13、sion on Trade and DevelopmentUNDPUnited Nations Development ProgramUNESCOUnited Nations Educational,Scientific and Cultural OrganizationUSDUnited States DollarWBWorld BankWDIWorld Development Indicators8Liberia is a post conflict country that is still in transition with a rapidly growing population
14、and notable rural-urban migration.The country is well-endowed with natural resources and conditions favorable for tropical agriculture that are supposed to significantly support its growth.Although Liberia experienced strong economic growth since the mid-1950s that continued into the mid-1970s,prope
15、lled primarily by the contribution of an export boom in iron ore and natural rubber and a stable political environment,this growth is believed to be below the countrys full potential.This could have been due to some underlying constraints that are hindering the country from attaining optimal growth
16、levels.In 2012,the Government of Liberia published its national strategic vision,Liberia Rising 2030.This plan is designed to enable Liberia to achieve middle-income country(MIC)status by 2030 through peaceful and inclusive politics,stable institutions,economic diversification,and accelerated human
17、capital formation.With rapid population growth and sluggish growth below the countrys potential,it will be very difficult for the country to achieve the set mile stone by 2030 without taking measures to understand the binding constraints to the countrys growth.Therefore,this growth diagnostics study
18、 is a useful tool for the government of Liberia to better understand the countrys problems impeding growth and to formulate a focused development strategy in the face of limited resources.The study report can also greatly help the government and its development partners to set priorities in their op
19、erations,thereby maximizing the impact of their assistance to the country.This study underscores the importance of diagnosing growth,and its binding constraints holistically.In doing so,the study adopted a modified growth diagnostic approach that takes conflict and political stability issues and all
20、 available official data to identify major growth constraints in Liberia.The major binding constrains identified in each category of the analysis(supply,demand,sectoral level;at micro and macro level,which includes durable peace)are fully discussed.As one of the main objectives of the government as
21、outlined in the Pro-Poor Agenda for Prosperity and Development is to provide greater income security to an additional one million Liberians and reduce absolute poverty by 23 percent across 5 out of 6 regions-through sustained and inclusive economic growth,driven by scaled-up investments in agricultu
22、re,in infrastructure,human resource development,and social protection.The African Development Bank believes that this is possible if the country has a better understanding of what is holding back its full growth potential.The findings of this study will inform the next African Development Banks Coun
23、try Diagnostic Note for Liberia,which will,in turn,inform the next African Development Banks Country Strategy Paper for Liberia.At the national level,this report can be a critical input into the joint government and donor study on the“future drivers of sustainable and inclusive development in Liberi
24、a”,a major study that is meant to underpin the next national medium term development agenda for Liberia.Hon.Samuel D.Tweah,Jr.Mr.Benedict S.Kanu Minister of Finance and Development Country Manager,Liberia Country Office Planning African Development BankForeword9Tis growth diagnostics study was finan
25、ced by the African Development Banks Liberia country office with technical support from the Country Economists Department(ECCE)of the African Development Bank.This study report was produced under the overall guidance of Benedict S.Kanu,Country Manager,Liberia Country Office of the African Developmen
26、t Bank.The Acting Lead Economist for Anglophone West African Countries in the West African Regional Business Deliver Unit(RDGW),Zerihun Gudeta Alemu,ensured the technical soundness of the report.The study was directly supervised by Yusuf Bob Foday,Senior Country Economist for Liberia.The following A
27、frican Development Bank staff provided valuable comments that helped to improve the quality of the report:Audrey Chouchane,Lead Economist;Sara Bartin,Chief Country Economist,Duncan Oman,Senior Country Economist and Martin Wafula Nandelenga,Senior Macroeconomist.The Bank would like to express its gra
28、titude for the support provided by the Research,Policy,and Planning Department of the Central Bank of Liberia.In particular,sincere thanks are due to Mr.Michael D.Titoe,Jr.,Assistant Director of the Macroeconomic Forecasting Unit of the Research Department for providing some data for the study.Simil
29、arly,thanks go to Mr.Mamdou Ndion,Senior Economist,World Bank,Liberia Country Office,for also helping with macroeconomic data for the study.The Bank gratefully acknowledges the significant research input of Prof.Alemayehun Geda of the University of Addis Ababa who served as the lead consultant for t
30、his study.The African Development Bank appreciates the valuable administrative support provided by John Alcorolson Tamba,Administrative and Finance Assistant and Lovette Poleynoh Merchant Topoh,Secretary to the Country Manager,both staff of the Banks Liberia Country Office.Acknowledgements10Executiv
31、e SummaryA Growth Diagnostic Study for LiberiaStylized facts of growth in Liberia1.Liberia experienced strong economic growth since the mid-1950s that continued into the mid-1970s,propelled primarily by the contribution of an export boom in iron ore and natural rubber and a stable political environm
32、ent.As a result,the average annual growth rate was remarkable,being more than 7 percent from 1955 to 1975(World Bank,1912).However,this began to decline in the 1970s to 3.5 percent,and further to an average annual growth rate of negative 0.8 percent in the 1980s,(AfDB,2022;Feenstra et al,2021,Penn W
33、orld Tables Data).This was chiefly due to worsening external terms of trade and growing economic mismanagement that was expounded by a debt burden that included a growing level of external arrears.The latter led to a breakdown of relations with international creditors and donors(World Bank,2018;UNCT
34、AD,2000).2.Following the intense conflict,the country has experienced since the early 1980s,Liberias growth in the last four decades has been shallow and volatile.This pattern was generally the outcome of political instability and intense conflict/civil war.The growth challenge became severe followi
35、ng the outbreak of the civil war that had been brewing since the early 1980s.After this period,Liberia has suffered from low and significant economic growth variability.The average annual growth rate decelerated to negative 0.8 percent in 1980s and to negative 8.3 percent in the 1990s(AfDB,2022;Feen
36、stra et al,2021,Penn World Tables Data).Growth recovered with an average annual growth rate of 8 percent between 2000-2010 but declined to an average yearly rate of 3.4 percent in 2010-2019,before the onset of the COVID-19 pandemic in 2020.In 2020,GDP contracted by 3 percent.3.Even if political stab
37、ility is attained through political settlement,as was the case before 1979(through the consolidation of an autocratic order)or through democratic election(since 2005),Liberias growth is significantly dependent on its external sector,in particular,on export growth,and sustained inflows of ODI and FDI
38、.This underscores the importance of diagnosing growth,and its binding constraints holistically.Accordingly,this study employed a modified growth diagnostic approach to take conflict and political stability issues and all available official data to identify major growth constraints in Liberia.The maj
39、or binding constrains identified in each category of the analysis(supply,demand,sectoral level;at micro and macro level,which includes durable peace)are the following:Supply,demand and sectoral sources of growth and their challenges4.From the supply side analysis in this study,it is found that at th
40、e macro and sectoral level,the major binding constraint to growth in Liberia was/is the challenge of low capital accumulation,which in turn is related to its low return.However,this is found to have a sectoral dimension.While labour productivity and hence return to labour is problematic in the servi
41、ce sector,it is return to capital that is found to be a significant problem in the non-service sectors at a macro level(this was more relevant for the industrial sector in particular).115.In terms of ranking,addressing the constraint in the service sector first will significantly impact spurring gro
42、wth.This is because one of Liberias primary growth sources has been a structural transformation(both static and dynamic).Therefore,through diversification to the industrial and service sectors,structural change will likely also be a major factor in spurring growth in the future.However,the service s
43、ector,to which labour is moving,is characterized by low and negative productivity growth.This pattern implies that a lack of investment in sectors with relatively higher labour absorptive capacity(e.g.,manufacturing)and human capital development to address skill gaps are among the binding constraint
44、s for structural transformation-led growth in Liberia.In addition,channelling more investment to the industry could have been further constrained by the low and declining marginal return of investment in this study.Thus,addressing these twin constraints(investing in industry/manufacturing and addres
45、sing the skill gap in the labour market)is key to spurring growth in Liberia.6.Among the sub-sectors within the service sector,and from a static structural change perspective(the within productivity effect),focusing on low productivity sub-sectors(starting from trade services)and removing their bind
46、ing constraints needs a priority.This will have the most significant impact on spurring growth.This is because increasing the productivity of sectors with high productivity growth is usually more complexthan raising the productivity of those with low productivity,as the former requires moving them i
47、nto a higher productivity ladder and product sophistication.The latter is invariably costly and takes time to invest in physical and human capital development and managerial and market development,which are crucial to attaining it.In addition,investing as a priority in this sector is broad-based as
48、the sectors(agriculture ad services)share in GDP is the highest.This justifies focusing on these low-productivity sectors with significant potential in the short run.7.Next to the service sector,the agriculture sector,as well as the construction sub-sector within the industrial sector are sectors ch
49、aracterized by lower productivity growth,as can be read from within productivity conditions.Raising productivity in these sub-sectors will substantially affect growth because a significant share of the countrys labour forceis employed in the agriculture and these sub-sectors,the percentage of employ
50、ment in the agriculture sector alone being about 43 percent of total employment,despite their low productivity growth.8.From the demand-side analysis,given the limitation of basing Liberias growth on the expansion of domestic demand that is related to Liberias small size,as well as given the growing
51、 negative effect of net exports on growth,addressing the binding constraints to exporting and engaging in export diversification that includes trade facilitations are very important.The import substitution of some essential goods must complement this.This will have the dual effect of increasing expo
52、rts and minimizing Liberias dependence on the primary commodities,favourable terms of trade and external assistance that make its growth and macroeconomic stability highly vulnerable to the external sector and related shocks.9.In sum,from the supply side,the major challenges of growth and the policy
53、 lessons to be drawn to address them are the following.First,by addressing its major binding constraints,reversing the declining trend of per capita output and productivity growth in the agricultural sector will significantly contribute to national productivity and economic growth.Second,the result
54、also implies that raising sectoral productivity in the service sector(and its sub-sectors),by addressing their binding constraint,is crucial to greatly impact growth in the very short 12run.Finally,the findings also show that since 2005,labour has not moved to sectors with rising productivity or lef
55、t sectors with low or negative productivity growth.The latter indicates a lack of dynamic productivity,especially in the agricultural,manufacturing and transport sectors.Effecting a structural transformation that changes this observed pattern is crucial to raise national productivity and achieving h
56、igh economic growth in Liberia.Macro and Micro level risks as challenges of growth in Liberia10.The first binding constraint to growth identified,related to low social return,is the lack of the human capital necessary to tap into the countrys growth potential,including implementing appropriate econo
57、mic policy.The challenge of weak human capital could be addressed by carefully designing a comprehensive financing framework for educational investment that takes on board the dependence of the tertiary level on investment in the high school level,in particular.Investing in the secondary education l
58、evel also needs to focus on producing a labour force with middle-level skills,such as through TEVT.The effort to expand and improve the tertiary sectors,which is found to be at a lower level of development,also needs rationalization of investment(including perhaps controlling corruption).This is bec
59、ause relatively higher investment has been made in the tertiary than secondary level,yet the outcome is low.It is also essential to examine the possibilities of tunning the nature of the growth of the labour force to the emerging demand for labour in the economy.11.Liberias growth is also identified
60、 as being vulnerable to external shocks,including shocks related to global commodity prices,external capital inflows,and the pandemic effect from a macro perspective.This adversely affected its macroeconomic balances and could be a risk factor to private-sector economic agents.12.Related to the abov
61、e,Liberias macroeconomic stance in the last decade was characterized by a significant gap between investment and domestic saving and a related trade deficit(and balance of payment deficit).Domestic resource mobilization(domestic saving)was deficient,especially considering the high investment-to-GDP
62、ratio.This pattern indicates the vulnerability of the macroeconomy(including growth)as the level of total investment is very high and needs significant external financing to sustain it in the future and derive growth.Thus,it is imperative to note that this macro vulnerability will be particularly se
63、vere if the government fails to pursue an informed and forward-looking prudent macroeconomic management and policy to cope with such vulnerability by monitoring them ahead of time.Public sector capacity building for this is a policy direction to be pursued.13.In addition,economic agents in Liberia h
64、ave also encountered micro-level risks/challenges that adversely affect their private appropriability and,hence,constrained national growth.The major micro-level challenges(risk factors)identified in includes:(a)ease of access to land,(b)ease of access to finance at a reasonable cost,(c)challenges o
65、f control of corruption,(d)the challenge of low productivity and low employment creation by the majority of firms in Liberia which are very small in size and,generally,not formalized,and(e)the enclave(limited-linkage with the rest of the economy)nature of the production activity of big firms engage
66、in mineral and exporting sectors.This has limited their potential positive effect on the broader economy and,hence,more general job creation,which is central to poverty reduction.1314.The study has also examined if a high cost of finance might have led to low appropriability for the private sector a
67、gents and acted as a binding constraint for growth.As a result,the following major problems that are related to the high cost of finance are identified that need an appropriate policy to address them:i.First,it has a high cost of finance and a limited supply of credit to the private sector by region
68、al standards.Though there is no systemic risk,the banks high level of non-performing loans(NPL)is worrisome.ii.Second,the financial system is found to have limited resources due to a low level of domestic savings.This has made credit to the private sector small and costly.We also found a strong nega
69、tive correlation between the lending rate and private investment.iii.Finally,it is also found that private capital inflows in Liberia,which FDI dominates,are minimal compared to its peers in the region.FDI,the countrys dominant form of private capital,is concentrated in the enclave exporting sector.
70、Public appropriability:Centrality of inclusive politics and growth for growth and its sustainability15.Public appropriability and growth:stable political environment was a pre-requisite for growth in Liberia,as its growth history shows.This underscores the decisive role of political stability and du
71、rable peace(public appropriability)for growth and its sustainability.The latter is related to inclusive economic and political governance for its own sake,as it is vital for durable peace(not simply for its effect on private appropriability).This,in turn,is related to building state capacity and str
72、engthening the countrys political and governance institutions to address challenges of“voice and accountability”and corruption.These are policy directions implied by this study.This is crucial because failure to do so could lead to a conflict relapse,reversing the tremendous growth attained since 20
73、05.14151.Liberia is a small open economy in West Africa.The estimates for 2022 show a population of 5.3 million people,with a GDP per capita of USD 673 in 2021.The country enjoys a rich history as being the first to gain independence in Africa in 1847.It is bordered by Cote dIvoire,Guinea,Sierra Leo
74、ne,and the Atlantic Ocean.Liberia is endowed with natural resources,including arable land and a climate suited for various food crops,including rice and cassava,and exportable cash crops such as rubber,coffee,cocoa,sugarcane,oil palm,cassava,fishery,as well as rich tropical rainforest reserves,a fav
75、ourable geographic location,a long coastline and the Atlantic Ocean.The country also has minerals such as iron ore,diamonds,and gold(World Bank,2018;UNCTAD,2000)1.2.Politically,Liberia is a unitary democratic republic,with the President as the head of state and government.Elections are held after ev
76、ery five years.The current President of Liberia,George M.Weah,was elected democratically in 2018,following the end of the two terms of the countrys first democratically elected female president,Ellen Johnson(2006-2018).The next presidential and legislative elections are due to be held in October 202
77、3.Despite the success in carrying out democratic elections since 2005,governance,including challenges of control of corruption(with a rank of 8.7 percent,2019)and government effectiveness(with a rank of 30 percent,2019)remain a challenge,with a potentially detrimental effect on growth,as well as soc
78、ial and political progress(discussed in detail in this document).3.Liberia experienced strong economic growth since the mid-1950s that continued into the mid-1970s,propelled primarily by the contribution of an export boom in iron ore and natural rubber and a stable political environment.The average
79、annual growth rate was remarkable,more than 7 percent from 1955 to 1975(World Bank,2012).However,this began to decline in the 1970s to 3.5 percent,from the highest growth rate of 6.5 percent in 1970,and further to an average annual growth rate of negative 0.8 percent in 1980s,this being at its lowes
80、t of negative 6.3 percent in the 1980,(AfDB,2022;Feenstra et al,2021,Penn World Tables Data).This was primarily due to worsening external terms of trade and growing economic mismanagement,expounded by a debt burden that included increasing external arrears.The latter led to a breakdown of relations
81、with international creditors and donors(World Bank,2018;UNCTAD,2000;Figures 1 and 2.4 below).4.The growth challenge became severe following the civil war outbreak brewing in the early 1980s(Figure 1).After this period,Liberia has suffered from low and significant economic growth variability ranging
82、from a negative growth rate of 51 percent in 1990,to a positive and high growth rate of 37.5 percent in 2007,according to AfDB data discussed in detail below(Figure 1).Compared to the 1980s,the average annual growth rate decelerated to negative 8.3 percent in 1990s2(AfDB,2022;Feenstra et al,2021,Pen
83、n World Tables Data).Growth recovered,with an average annual growth rate of 8 percent between 2000-2010,but declined to an average annual rate of 3.4 percent in 2010-2019,before the onset of the COVID-19 pandemic in 2020.In 2020,GDP contracted by 3 percent-lower than the average African contraction
84、of 2 percent and doubled its GDP contraction of 1.4 percent the year before.IntroductionChallenge of Growth in Liberia1 The literature on resource rich commonly follows the World Banks(2019)classification of countries as resource-rich or resource-scarce.Resource-rich countries are those where fuel a
85、nd mineral exports contribute over 20 percent to their gross domestic product(GDP).Liberias mineral and rubber exports as share of GP qualify it as resource rich and hence with significant potential for growth(see Yimer,2022).2 In both AfDB(2022)and Penn World Table data,the 1997 growth rate is an o
86、utlier rate of 106.3 percent is replaced by the 1996 growth rate of 12.1 to arrive at this reported rate which gives a better picture of the average growth rate of the decade.Its inclusion puts the decades growth rate at 1.1 percent instead.If 1997 is excluded,the average growth rate of the decade w
87、ill be negative 10.6 percent.165.The Macroeconomic environment during these episodes of growth in the last two decades has been generally good in the 1990s,with a slight improvement in 2000-2009.This has begun to deteriorate in the decade since 2010,especially since 2017.The average annual inflation
88、 in the 1990s was 10.2 percent.This declined slightly to 9.6 in 2000-09,but increased to 12.1 percent in 2010-2020.Similarly,another macro indicator,the overall fiscal deficit,which was 0.9 percent of GDP in 2001-2009 deteriorated to-5.5 percent of GDP in 2010-2020.The rising level of inflation and
89、fiscal deficit in the last decade was primarily attributed to conditions in the last three years of the decade(2018-2020)where the economy was hit by the external shock of COVID-19 in 2020 and the Ebola virus(2014-2015)and the decline in global commodity price before that(2013-2015).With significant
90、 dependence of the country on the external sector(FDI,ODA and primary commodity exports)for financing its growth and a weak financial sector with poor performance in mobilizing domestic resources(gross domestic saving as a share of GDP between 2011-2020 being 6.5 percent,while the investment to GDP
91、ratio in the same period stood at 43 percent),Liberias growth is also vulnerable to external shocks that may come from the global economy.6.Regarding recent growth performance and its prospects,according to the Central Bank of Liberia,2021(CBL 2021,henceforth),GDP growth has recovered from the negat
92、ive growth in 2020,growing at 4.2 percent in 2021,and is also estimated to growth by 4.5 percent in 2022.Moreover,with inflation declining to a single digit of 5.5 percent in 2021,down from 13.1 percent in December 2020;and current account deficit slightly improving to 17.4 percent of GDP in 2021,fr
93、om 17.9 percent in 2020(CBL,2021),Liberias macroeconomic outlook has also improved(CBL,2021;World Bank,2022).Similarly,the World Bank(2022)projected Liberias GDP to grow by 4.4 and 4.8 percent in 2022 and 2023,respectively.AfDB projects growth at 3.5 percent in 2022.7.Despite Liberias potential reso
94、urces(that include a young labour force),its recent growth and encouraging prospects,as alluded to above,Liberia remains among the worlds poorest countries.In 2021,its international(headcount)poverty rate stood at 44 percent(using a poverty line of USD 1.9 in PPP terms).The poverty rate becomes a st
95、aggering 75.6 percent at the poverty line of USD 3.20 in PPP terms(Word Bank,2022).Similarly,with a Gini coefficient of 0.35,Liberias inequality is also extremely high.The human development index(HDI)for Liberia,which was 0.48 in 2019,is also one of the lowest in Africa.In addition,as discussed in d
96、etail in chapter three,other indicators of human development related to the educational outcomes in primary and secondary education are very low and did not show significant improvement in the last two decades(UNDP,2022).This is partly attributed to the legacy of its devastating conflict and poses a
97、 significant challenge to its growth.8.Finally,since Liberia is a resource-rich yet conflict-ridden country in its recent history,it is imperative to investigate its major growth constraints by analysing why a resource-rich country failed to exploit that potential fully.Furthermore,related to the fi
98、rst,the second question is why was Liberia conflict-ridden,and what was the effect of conflict on growth?The broad answer to this is first,it lacks the human capital necessary to tap into its potential and implement appropriate economic policy.Liberia ranks 175th in the human development index(HDI)a
99、mong 190 countries(2021).The countrys human development index in 2021 was 0.48,and the dependency ratio was 71 percent in the same year.This HDI index means children born today in Liberia can be expected to be only 48 percent as productive when 17they grow up(see section 3 below).This is aggravated
100、by a lack of inclusive growth(World Bank,2012)and politics,generally a recipe for conflict and unsustainable growth.Thus,this study attempts to unravel these and related answers by exploring the binding constraints to growth at the macro,sectoral and micro levels.Method of Analysis in Brief9.The ana
101、lysis is based on Hausmann et als(2005)Growth Diagnostic Approach(GD approach,henceforth).The GD approach attempts to identify major binding constraints to growth and prioritizes them for policy action.The prioritization exercise is guided by identifying the most significant growth constraints,assum
102、ing that relieving them will positively affect growth.The GD approach assumes potential growth constraints are strongly associated with all the factors of production and the return to each of them in the accumulation process.The approach,then,organizes these constraints under the problem of low appr
103、opriability(low factor return)to the private sector.The low appropriability condition is hypothesized to limit private economic agents engagement in economic activity,which stifles growth.Thus,easing these binding constraints,by contrast,is assumed to spur growth.These binding constraints are organi
104、zed under three categories:low social return,macro and micro levels risks(market and government failures),and high cost of finance.These are summarized in Figure Ia.The low social return to factors of production is related to insufficient investment in complementary factors like human capital and in
105、frastructure or could be related to poor geography.The micro and macro-level factors are related to the risks associated with macroeconomic imbalance,tax structure,high tax rates,insufficient property rights and contract enforcement,etc.Finally,the high cost of finance is assumed to include a high c
106、ost of lending,poor intermediation,low domestic savings,limited access to external financial markets,or low foreign direct investment(FDI)etc.(World Bank,2006;Hausmann et al.,2005;AfDB,2015,AfDB,2008,Figure Ia).Figure Ia:The Growth Diagnostic Approach Source:AfDB(2008)High cost financeLow appropriab
107、ilityLow social returnsLow returnto economic activityProblem:Low levels of private investment and entrepreneurshipbad infrastructurePoor geographylow human capitalgovemment failluresmarket faillureslow domestic savingpoor intermediatioinformationexternalities:*self-discovery*coordinationexternalitie
108、smicro risks:property rights,corruption,taxesmacro risks:financial,monetary,fiscal instabilityBad internationalfinanceBad local finance1810.The GD approach then proposes using various tests to identify constraints and how a change in these constraints would lead to a change in investment and growth,
109、as well as determining how some economic agents bypass these constraints in a non-optimal manner.The GD approach starts at the top of a decision tree,such as in Figure 2.1 below,moving progressively downward in this decision to subsequent lower branches,depending on the answer to the question raised
110、 in the upper part of the decision tree.This procedure is pursued iteratively across the three noted categories of binding constraints.This is aimed at identifying and prioritising the binding constraints in each stage.In addition,the approach employs a comparative analysis of the countrys performan
111、ce with comparator countries(benchmarking countries)for identifying and prioritizing these constraints(World Bank,2006;Hausmann et al,2005;AfDB,2015 Hausmann,Klinger and Wagner,2008).For this purpose,selected West African countries are used as comparator countries to gauge the situation in Liberia.S
112、ierra Leone,Guinea,Guinea-Bissau,Togo and the Gambia are chosen for this purpose.These methods are essential to identify and prioritize the binding constraints to Liberias growth.This approach is already successfully deployed for a previous AfDB growth diagnostic study for Rwanda(AfDB,2021).11.One w
113、eakness in using the standard GD approach in the African context is its failure to consider the political-economic context of the country,which includes issues related to governance and conflict.Liberias growth history shows that understanding conflict and the role of democratic and inclusive politi
114、cs for growth is essential to uncover the root cause of growth challenges in Liberia(see Chapter I).In addition,improving governance and building institutions are crucial for growth and its sustainability.Thus,investing in the socio-political sphere and institutional building is vital for sustainabl
115、e development.With this idea and the critical literature to the GD approach (see Annex 1),the standard GD approach is modified in this study by including this crucial dimension of growth and development in Liberia.This new addition is labelled public appropriability and is discussed in Chapter 6.In
116、short,this modification of the method will help us address the importance of inclusive growth,inclusive politics and durable peace for sustaining growth in Liberia(see Figure 2.1 and Annex 1 for details).12.With this background,the rest of the report is organized as follows.Chapter one examines the
117、stylized facts about growth and its challenges in Liberia.This will be based on Liberias growth literature in the last four decades.This analysis is placed in the broader political-economy context of the country,as conflict and lack of durable peace are also one of the major binding constraints to g
118、rowth and growth sustainability in Liberia.This is aimed at drawing lessons for this study.Chapter two begins by identifying the return to factor accumulation and its effect in limiting growth at the macro-level.The latter requires understating growth challenges both from the demand and the supply s
119、ide,including sectoral growth and the related issue of structural transformation.This is followed by chapter three,where a low return to private sector accumulation(private appropriability)as binding constraints to growth is discussed.The latter is related to low private appropriability due to“low s
120、ocial return”as the binding constraint to private investment and growth,which is discussed in part three in detail.Low private appropriability is also related to“macro and micro level risks”to the entrepreneurs,which is discussed in chapter four.The high“cost of finance”is another binding constraint
121、 addressed in chapter five.By recognizing the decisive effect of political economy conditions that includes conflict and governance on growth in Liberia,chapter six will discuss these issues under the concept of“social appropriability”.19Thus,chapter six examines the importance of inclusive growth a
122、nd inclusive politics and their effect on durable peace for sustaining growth in Liberia.Chapter seven concludes the study.201.1 Brief Political and Growth History of Liberia13.For over a hundred years before 1980,Liberia was controlled politically by the minority descendants of the original African
123、 American settlers that came first in 1820 from the USA.Leaving the countrys long history since then aside,the violent overthrow of this minority ruling elite in 1980 led to political instability marred by civil wars(1989-2003),with devastating implications for the countrys growth and development(Fi
124、gure 1).The war began following the coup detat in 1980 and lasted until the establishment of a transitional government following the peace agreement in 2003.The Peace Agreement was signed in Accra,Ghana,between the Government of Liberia,the Liberians United for Reconciliation and Democracy(LURD),the
125、 Movement for Democracy in Liberia(MODEL)and other Political Parties.This was followed subsequently by a democratic election conducted in 200514.The Tolbert and Liberia Party Regime and Growth:President William Tolbert,the last president of the historically ruling elite(the Americo-Liberians),came t
126、o power in 1971.He pursued a policy of suppressing opposition until his final days in 1980.This included killing protestors of the harsh economic situation at the end of the 1970s.The governments violent suppression of the protest finally led to a military coup dtat in April 1980,where Tolbert and i
127、ts prominent ministers were executed,marking the end of Americo-Liberian domination of the countrys political power.In tandem with this political development,Liberias growth history showed robust growth in the 1960s.Growth also remained positive throughout the 1970s,except in 1975,-the average annua
128、l growth during the 1970s(1970-1979)being 3.5 percent.This growth period,which is related to the politically stable period,ended in 1980 when GDP contracted by 6.3 percent,which,in turn,is related to the 1980 coup dtat(Figure 1).Generally,before 1975,growth was over 7 percent per annum for 1955-1975
129、,with per capita GDP peaking at USD 840(constant 2000)in 1972(World Bank,2012).However,this excellent growth collapsed by 1980(Figure 1).15.The Doe Regime and Growth:The Samuel Doe military regime(1980-1990)that followed became repressive and corrupt.As a result,internal unrest,opposition to this mi
130、litary regime,and governmental repression steadily grew.This situation continued until 1989,when Liberia sank into an outright civil war.Doe had to put down about seven coup attempts between 1981 and 1985.He also began to give key government positions to those who belonged to his ethnic group,changi
131、ng the conflict to take an ethnic form.The US aid cut and the uprising across the country began to shorten the regimes days.Political instability and negative and low growth(Figure 1)became the main feature of the regimes growth history.This period also coincides with the period that Charles Taylor(
132、the future President)unleashed an uprising which was also joined by various warring factions that increasingly began to organize along ethnic lines.By the middle of 1990,Taylor controlled much of the country and laid siege to Monrovia;and on September 9,1990,Doe was killed by rebels,ending his Polit
133、ical Context and GrowthI21regime.Unaspiringly,the average annual growth in this period(1980-1989)was-0.8 percent,oscillating between negative(as low as negative 6.3 and 3.4 in 1980 and 1983,respectively)and positive growth rates(that were 2.8 percent when it was highest in 1989 and 1990).Thus,in add
134、ition to the near-zero average annual growth,the Samuel Doe regimes period(1980 to 1990)was also characterized by significant growth variability(Figure 1).Figure 1 Evolution of Liberias GDP growth(1965-2019,exl 1997 growth of 106.3%)Source:AfDB(1990-2021)and Pen World Tables(1965-1990),2022.16.The T
135、aylor Civil War Regime:1991 to 2003 was a turbulent period in Liberias recent history.The first half of the 1990s was characterized by an attempt to sign a peace treaty by the various parties in conflict.This was followed by the period(1996-2003)marked by clashes and rebellion against the government
136、,the fleeing of Charles Taylor,a peacekeeping operation established by Security Council resolution 1509(2003)of 19 September 2003 that completed its mandate on 30 March 2018,and various peace efforts spearheaded by ECOWAS and UN.All these efforts were unsuccessful due to the existence of various fac
137、tions in the conflict and their irreconcilable interests.The period thus marked the beginning of the countrys second civil war,from 1997-2003.This conflict ended briefly in 1997 when Charles Taylor won the election with a landslide(75.3 percent),and the runner-up,Unity Party leader,Ellen Johnson Sir
138、leaf,received a mere 9.58 percent.Until 1999,conflict subsided considerably,though it was not stopped,as insurgencies were fighting with Charles Taylor.He also unleashed repression,including killing opposition figures that further triggered the civil war.In 2003,Liberian women engaged in peaceful pr
139、otests across the country and were able to make Taylor part of the peace process.Rebel groups also began to control two thirds of the country.The Womens struggle,helped by the rebellion against Taylor,led to peace negotiations,and finally,peace in Liberia after an intense and gruesome 14-year civil
140、war that left an estimated 250,000 dead and over 1 million displaced.This process helped 50,01847-1980(Liberia Party)Tobert&his ministerskilled by Does Coup in1980Couptdetat bySamuel DoePeacetreatysignednotheld30,237,5-30,1-51,0-6,3-3,9Ellen JohnsonelectedElection ofGeorge WheaClashes,WomanProtest,T
141、aylorflee,PeacekeepingoperationTaylor&othersUprising40,030,020,010,0-10,0-20,0-30,0-40,0-50,0-60,0958739200072009200,022bring to power the countrys first democratically elected female head of state,Ell
142、en Johnson Sirleaf,in 2005.17.During this turbulent period,Liberia saw the lowest growth rate in its recent history.The average annual growth rate of-0.8 percent in the 1980s decelerated sharply to-8.3 percent in the 1990s.In addition,this turbulent period was characterized by high growth volatility
143、.This reached as low as negative 51 percent in 1990 and as high as 30 percent in 1998,which followed the end of the first wave of the civil war in 1997(Figure 1).During the first eight years of the civil conflict in the 1990s,the economy came to a standstill,and central political authority collapsed
144、.As a result,the delivery of public services that included education and health stopped.This situation has led to the shrinking of the economy by about 60 percent of its pre-war level(UNCTAD,2000).From this brief history,it is imperative to note how conflict is Liberias number one binding constraint
145、 of growth.18.Peace,The Democratic Regimes and Growth:Two periods of growth episodes could be observed following the second-largest collapse of GDP growth to negative 30 percent in 2003.The year 2003 marks the end of the conflict year and the beginning of the post-conflict period(Figure 1).The first
146、 episode of high growth is observed under the administration of the first democratically elected president of the country,Ellen Johnson Sirleaf,in 2005 a president who served two terms between 2006-2018.The second episode of the low growth period followed the end of the Ellen Johnson Sirleaf Adminis
147、tration and the election of the current President George Weah(2018-to date).19.Considering the progress made towards peace during the years just before the election in 2005,the Chairman of the transitional government,Charles Gyude Bryant requested an end to the UN embargo on Liberian diamonds(that w
148、as imposed since March 2001)and timber(set since May 2003).However,the UN Security Council postponed such a move until the peace was more secured and because of the failures of the Transitional Government to curb corruption.Later,in September 2005,the Liberian government and the International Contac
149、t Group on Liberia signed an anti-corruption program.The peace talks and the final peace deal were also established due to the concerted efforts of both regional and global actors,including ECOWAS,Benin,Gambia,Ghana,Guinea-Bissau,Mali,Nigeria,Senegal,Togo,Nigeria,the UN and USA.20.By June 2004,a pro
150、gram to reintegrate the fighters into society began;the economy also began to recover somewhat in 2004,with GDP growing at 2.6 percent,bouncing back from the negative 30 percent growth rate in 2003(Figure 1).By years end,over 100,000 Liberian fighters had been disarmed.The transitional government al
151、so conducted fair and peaceful democratic elections on October 11,2005,where President Ellen Johnson Sirleaf was declared the winner on November 23,2005,in an election where the current president and former international footballer,George Weah,also took part.President Ellen Johnson Sirleaf took offi
152、ce on January 16,2006,becoming the first African woman to do so.In June 2006,the United Nations ended its embargo on Liberian timber(effective since May 2003)but continued its diamond embargo.Following the end of the two terms of President Johnson-Sirleaf in 2018,President George Weah was elected be
153、coming the second democratically elected president of the nation after the war.2321.During this period of democratic regimes,GDP growth recovered,becoming positive,though significantly variable(Figure 1).Following the first election,GDP grew by 5.3 percent in 2005,double the growth rate a year befor
154、e in 2004.During President Ellen Johnsons administration,GDP grew by an average annual rate of 8.2 percent(2005-2017).In some of the years,the growth rate was as high as 13.5 and 37.5 percent,as in 2006 and 2007,respectively(Figure 1).Growth began a declining trend following the election of Presiden
155、t George Weah at the end of 2017.Thus,during 2017-2021,average annual GDP growth became nearly zero(0.04 percent).This is largely attributed to the decline in global commodity price that started in 2013 and effect of two health pandemics:the Ebola and COVID-19.The later led to a negative growth rate
156、 of 3 percent in 2020.Recovery in growth began in 2021,when GDP grew at 3.3 percent in 2021,primarily driven by growth in mining and construction sectors on the supply side and public spending on the demand side.22.What is the lesson from this brief history of the political economy of growth for und
157、erstanding the binding constraints of growth in Liberia today?What were the stylized facts of growth and the primary drivers of this growth in Liberia?Three main stylized facts could be distilled from the analysis,which are briefly discussed below.a)First,one of the major features of growth in Liber
158、ia is that political conflict and lack of durable peace had a disproportionately high negative effect on growth-the average annual growth rate of-0.3 and-8.3 in the 1980s and 1990s being the evidence.This political and governance problem took the form of a civil war before democratic elections in 20
159、05 and became a governance problem that included corruption and government ineffectiveness since then.The lesson is that inclusive politics and durable peace are the major pillars of Liberias growth and sustainability.In addition,we noted that each episode of growth deceleration and acceleration is
160、strongly associated with heightening and dampening political conflict,respectively.b)Second,even if political stability is attained through political settlement,as was the case before 1979(through the consolidation of an autocratic order)or through democratic election(since 2005),Liberias growth is
161、significantly dependent on its external sector,in particular,export growth,and sustained inflows of ODI and FDI.This can be read from the average annual growth rate of 10.7 percent during 2005-2015,when export and external inflow growth coincided with the peace and political stability period(as well
162、 as between 1965-1975,where the economy was growing by over 7 percent,owing to conducive external sector and political stability).In contrast,growth decelerated to an average annual rate of-0.2 percent during 2016-2020(or to 0.5 percent if the COVID-19 year of 2020 is excluded),despite the political
163、 stability that prevailed.This is chiefly due to the adverse effect of the external shocks(Ebola,COVID-19 and global commodity price decline since 2013).c)Third,growth variability was a major feature of growth in Liberia.As can also be read from the erratic growth rate shown in Figure 1,the standard
164、 deviation of growth in the 1990s,2000s,and 2010s were 27.1,17.8 and 4.7,respectively(the mean growth for the same period being-8.3,8 and-0.2 percent,respectively).This significant growth variability is the combined effect of the above two stylized growth features in Liberia.24Thus,minimizing the ve
165、ry high growth variably alone could take the prospect of increased and sustained growth in Liberia a long way.23.Given these stylized facts of Liberian growth,our analysis in the rest of this study needs to identify the major factors that were drivers of such growth that rendered the stylised growth
166、 facts observed.Moreover,how binding are some of these factors still to spur and sustain growth in Liberia?Answering these questions requires,among other things,placing our growth diagnostics analysis in the broader political economy context of the country.1.2 Binding Constraints of Growth from Grow
167、th Diagnostic studies of Liberia24.Studies about economic growth in Liberia(World Bank,2021,2018,2012;IMF,2016;2017;MCC and GoL,2013,UNCTAD,2000)point at several constraints that are binding to growth in Liberia.These factors range from deficiency of human capital and governance problems to that of
168、external shocks.For example,the World Bank(2012)and IMF(2016,2018)conducted a comprehensive study of growth in Liberia.These studies found the following as major binding constraints to growth in Liberia:(a)lack of efficient allocation of resources owing to lack of coordination among economic agents
169、that includes SMEs;(b)deficient human capital that limited both inclusive growth and the ability to design informed policy and implementing it;(c)deficiency of entrepreneurs and lack of an enabling business environment that includes credit to SMEs,ease of doing business,property right security,bette
170、r land tenure system and better economic and political governance that includes eliminating corruption;(d)vulnerability of GDP growth and the macro economy to external shocks that includes commodity price decline,as well as health pandemics that include Ebola in 2014-2015 and COVID-19 recently(IMF,2
171、016;IMF,2021);and(e)conflict and state fragility that led not only to low and variability of growth,but also costing the country in terms of both physical and human resources,making growth and the macroeconomic stability very fragile(see also UNCTAD,2000;Alemayehu,2022).25.The growth-related studies
172、,briefly noted above,have also identified the following major constraints that need to be addressed so as to spur growth in Liberia(World Bank,2022;IMF,2016,2021;Andrews,2015;MCC and GoL,2013;Backiny-Yetna,et al 2012;UNCTAD,2000):invest in human capital and skills formation and avoid the mismatch be
173、tween demand for labour and its supply in a comprehensive manner,as this is the major binding constraint to growth(De Simone et al,2022;World Bank,2012;Beckiny-Yetna et al,2012;Sawyer 1992,cited in Munive,2011).Second,market failure and entrepreneurial deficiency is ridden by coordination failure th
174、at needs collective action to ensure self-discovery and realize the countrys potential and entrepreneurship of its people(World Bank,2012).Third,address the governance failure(land tenure,ease of“doing business”,credit provision etc.)that is hurting economic agents,both the SMEs and big companies th
175、at are addressing this in a roundabout way.Related to the latter,capacity building in a government institution that includes getting rid of(or at least reducing)corruption and a dysfunctional legal system is essential.Fourth,addressing the land tenure issue with a view to inclusive growth,specific l
176、aws,proper land management and tenure security are critical to this process(World Bank,2012;Clower et al.,1966,cited in Munive,2011).Fifth,raising productivity in the traditional sector and preparing a fertile ground for creating new opportunities and activities with profitability.Thus,productivity-
177、driven diversification,including combined export promotion and import 25substitution strategy,are vital factors for Liberias growth sustainability(World Bank,2012;2020;Andrews,2015).26.These findings are important for this study,not only to locate the results of this study in the context of existing
178、 growth studies about Liberia,but also,to identify the major binding constraints of growth in Liberia that need to be investigated further.They will also form the basis to identify other new developments since these studies were conducted.They also have the practical objective of informing growth-en
179、hancing policy choices available for the government and its development partners.262727.Identifying the return to factor accumulation and its effect in limiting growth requires understating growth challenges from different perspectives:the supply side,the demand side,the sectoral side and the relate
180、d issue of structural transformation.This diagnosis aims at identifying the major impediments to the best use of factors of production for high and sustained growth from all these dimensions.In all these dimensions,the incentive implications of the return to accumulation are related to productivity
181、growth and structural transformation.This section,thus,looks at these issues in Liberia to identify the binding constraints to growth and prioritize them for policy action from a macro perspective.The jargon of the Growth Diagnostic approach identifies them as the shadow price of the binding constra
182、ints for growth.This effort is,thus,guided by the first layer of the GD approach presented in Figure 2.1.Figure 2.1 adds a new category labelled Public appropriability to the standard approach.This aims to take on board the importance of durable peace and transition from state fragility to resilienc
183、e for sustainable growth in fragile states such as Liberia(see AfDB,2021;Alemayehu,2022 Annex 1 for details).Figure 2.1 The Growth Diagnostic Approach:The First Stage Source:Authors Modified Compilation based on the HRV(2005)Approach*Note:this item is not available in the standard GD approach but is
184、 introduced here,given its importance in the African context(Annex 1).Return to Factor Accumulation:Macroeconomic and Sectoral Level Growth DiagnosticsIIThe Growth Challenge&Low levle of Accumulationand EneterpreneshipLow Private Returnto Economic Activitylow privateappropriablityIdentifying the Sha
185、dowprice of the constraining factors(Low Public Appropriablity)Low Social ReturnMicro&Macro Level Risks(Market and Govt Failure)The Cost of Finance282.Diagnosing Liberias Growth and Its Implications for Return to Accumulation2.1.The Supply Side:Factor Accumulation and Growth28.Following the decision
186、 tree,as shown in Figure 2.1,the first stage of the GD analysis is done at the macro level.This is followed by a detailed analysis of the same at the sectoral level.For this purpose,a growth model for Liberia is specified and estimated.Details about this model are provided in Annex 2.Next,two varian
187、ts of growth models:an endogenous,as well as a human-capital,augmented Solow growth model for Liberia,are specified and estimated for the identification of return to factor accumulation for use in this part of the study(see Annex 2 for the model and estimations results).Various growth models were es
188、timated at the exploration stage and offered different values for the return to capital and labour.Such differences emanate from multiple factors,which include:variations in the theoretical model selected(e.g.,types of returns to scale chosen,for instance),the nature of the data used(see World Bank
189、versus Pen World growth data,for example),as well as the variation in the econometric methods,adopted(e.g.,Ordinarily Least Square/OLS or Auto-regressive Distributive Lag/ARDL models etc.).However,such result variations are common in previous similar studies(see AfDB,2021).Finally,after many experim
190、ents and an exhaustive search,this section uses the final model chosen for the growth accounting exercise.The model offers a capital share of 0.29 and a labour share of 0.71.The results using these parameters are presented in Table 2.1 and Figure 2.2.29.This exercise reveals that the average contrib
191、ution of labour,capital(together constituting factor accumulation)and total factor productivity(TFP)to growth in the last two decades had been 74,26 and 0.3 percent,respectively.However,this average hides the significant variation in the relative contribution of these factors of production across ye
192、ars.30.This exercise further shows the following:First,although the accumulation of labour is the dominant source of growth in Liberia from the supply side during the entire period,this has widely fluctuated over time:declining to about zero in 2000-2004,increased to 25 percent in 2005-2009,and furt
193、her to 63 percent in 2010-2014 and dropped again to 16 percent in 2015-2021.The contribution of labour declines(or increases)sharply whenever there is an abrupt change in growth rate that is related to eitehr intensity of conflict or external shocks.Such a sharp change in the contribution of labour
194、in such growth episodes is generally compensated by an opposite movement of the contribution of Total Factor Productivity(TFP).For instance,the contribution of labour sharply declined to 25 percent in 2005-2009,compared to its level of 69 percent in 2000-2004.This resulted from the abrupt growth in
195、GDP by 14 percent over the period(due to recovery from low base).The contribution of TFP explained 10 percentage points(74 percent)of this growth this reduced the contribution of labour accumulation to GDP growth in the period(Table 2.1;Figure 2.2).The period 2005-2009 relates to the peace period th
196、at was finally attained after a protracted and intense conflict for years;hence may explain the significant rise of the contribution TFP,which is usually computed as residual and picks the peace effect too.From the year 2010 onwards,the dominant and positive contribution of labour to growth remained
197、 strong,the only exception to this being the year 2015.29Figure 2.2 Evolution of the Contributions of Capital,Labour and TFP to Growth in Liberia (2000-2021,sum adding to one)Table 2.1 Growth Accounting for Liberia(2000-2021)Source:Authors Computation based on A Growth model,AfDB and Pen World DataN
198、ote:Capital stock data is from Pen World Table,and the effect is similar to another one generated using the perpetual method(The perpetual method-based capital stock is generated by adding the annual investment on the initial capital stock for 1964.The latter,intern,is generated using the average IC
199、OR value of Liberia for the years 1964-1968,which renders an ICOR value of 3.23.The beta coefficient from the estimated growth model,which is 0.29 for capital and 0.71 for labour is used for the analysis.The 2021 growth data is based on forecasts of AfDB and assumes the historical 2020 growth rate f
200、or capital and labour remains unchanged.Average Annual GrowthAverage Annual GDP GrowthContribution to Average Annual GrowthCapitalLabourTotal Factor ProductivityGrowth(2000-2021)4.11.13.00.01Contribution to Growth(%)(25.9%)(73.7%)(0.3%)Half-decade periods and Annual Growth AccountingGrowth(2000-2004
201、)-3.40.02.3-5.6Contribution to Growth(%)(1.2%)(68.5)(-167.4%)Growth(2005-2009)14.40.23.510.7Contribution to Growth(%)(1%)(25%)(74%)Growth(2010-2014)6.62.54.2-0.1Contribution to Growth(%)(37.7%)(63.3%)(-0.9%)20150.012.80.00-2.82016-1.62.34.9-8.820172.51.52.0-1.120181.21.02.0-1.82019-1.40.92.3-4.62020
202、-3.00.92.3-6.120213.30.92.30.2100%0,000,740,260,690,010,250,740,630,38-0,011,561,00-2,450,01-1,6780%-80%4.1%2000-2021K-ContnL-ContnTFP-20-2021-3.4%14.6%6.6%0.1%60%-60%40%-40%20%-20%0%3031.Second,for the period(2000-2021),capital accumulation followed labour in terms of si
203、gnificant contribution to growth,accounting for 26 percent of the growth in the period.However,its contribution in the last two decades has been only 35 percent of that of labour accumulation(Table 2.1).Its contribution remained positive sine 2005 the year of the peace agreement and democratic elect
204、ions.However,its contribution was negligible between 2000 and 2009 and became stronger after 2010,which continued until 2016.Since 2017,its contribution began to decline,yet remained throughout(Figure 2.2 and Table 2.1).Investment stagnation explains this result during the first decade of the last 2
205、0 years.The latter is understandable,as the fragility of the state characterized that period,and the country was at the initial stage of its recovery from the conflict.During this period(2001-2011),the average share of investment in GDP was 22 percent,and this was about half the average annual level
206、 of 44 percent between 2012-2021(AfDB,2022).32.In addition to the information in Table 2.1,the secondary and limited role of capitals contribution to growth could be further corroborated by Figure 2.3,which shows an alternative measure:the marginal return to investment(capital accumulation)in Liberi
207、a over the last two decades.The marginal return to investment(MRI)is approximated by the inverse of the incremental capital-output ratio(ICOR)for the same period.The result shows that the MRI was minimal and had a negative value for some years(Figure 2.3).The MRI first declined steadily from a posit
208、ive return of USD 0.54 per one USD investment in 2000,reaching the bottom where a dollar investment brought a loss of USD1.27 in 2003 years before 2003 being the conflict period where capital itself is destroyed,and the accompanied labour cannot be employed due to the conflict.This briefly recovered
209、 to an encouraging level of USD1.23 in 2007(a period of peace and political settlement that began in 2005).However,it began declining sharply and steadily thereafter a possible result of the inefficiency of capital use that might be related to governance problems and challenges of external shocks di
210、scussed in section three in detail(Figure 2.3,panel(a).The average annual Marginal Return to Investment(MRI)for dollar investment in the last 20 years was just USD 0.18.Generally,between 2000-2021,it has been declining by 5.5 percent per annum.This shows marginal and declining private appropriabilit
211、y,one of the primary factors that deter the private sector from engaging in productive economic activity.This points to the importance of focusing on constraints to capital accumulation and raising the return to capital to spur economic growth.31Figure 2.3 The Marginal Return to Investment(a)and Tre
212、nd of TFP(b)in Liberia (2000-2021)(a)Marginal Return to Investment (b)Trends of Total Factor Productivity Source:Authors computation based on the estimated growth model and Pen World Table data33.Third and finally,for the period as a whole,the average annual contribution of TFP to growth had been th
213、e least with an average annual contribution of just 0.3 percent for the period under analysis(2000-2021).TFPs contribution was also very volatile,ranging from a low of negative 31 percentage points contribution(to the-30.1 GDP growth in 2003)to a maximum of positive 33.5 percentage points contributi
214、on(to the GDP growth of 37.5 percent recorded in 2007).These extreme values correspond to the MRI of the two periods,as shown in Figure 2.3.In 2003,the capital stock per worker has reached the historic low level of US1000 at 2011 PPP,and hence,the lowest MRI(and the lowest TFPs contribution),while i
215、t reached its highest value of US 8500 at 2011 PPP in 2007(World Bank,2018)owing to a recovery in aid-financed investment and significant inflow of ODI following the peace agreement in 2005 leading to the highest positive MRI and TFPs contribution.In addition,in 2003,volume of exports had declined b
216、y 54 percent,while it had grown by 23 percent in 2007(from a 9.4 percent decline a year before)(AfDB,2022).This explains the extreme value of TFP in the two periods,as TFP is generally computed as residual and picks all such external development(be they positive or negative).Even leaving aside such
217、extreme values,Table 2.1 shows the significant volatility of the contribution of TFP to growth.34.In general,a deeper look at the trend of the contribution of TFP to growth over the last two decades shows a declining trend by an average annual rate of 0.17 percentage points(3.2 percent per annum)(Fi
218、gure 2.1).TFPs contribution was negative 5.6 percentage points(-167.4 percent)between 2000-2004 and turned to significant positive 10.7 percentage points(74 percent)in 2005-2009(Table 2.1).This has turned to about zero(-0.9 percent)between 2010-2014.The significant negative result in the first half
219、of the 2000s(just before the 2005 1,5040,0-40,0-31,533,530,0-30,020,0-20,010,0-10,01,32y=-0,0106x+0,3015R2=0,023y=-0,20 x+2,34R2=0,01-1,271,00-1,00-1,5020002000420052006200720082009200000002000420052006200720082009200132014
220、2000210,500,000,00-0,50(a)Marginal Return to Investment(b)Trends of Total Factor Productivity32democratic election and peace)is associated with the height of the conflict in the country,which disrupted economic activity,and GDP contracted by an average annual rate of 3.4 percen
221、t,as part of the countrys work force was engaged in the conflict.Understandably,capital accumulation during this period was also zero(Table 2.1).The contribution of TFP after 2015 was volatile and decelerated(Table 2.1).Between 2015-2021,the contribution of TFP was positive only in one of the seven
222、years.These negative values were very high(in absolute terms)too reaching as high as|-8|in 2016 and|-6|in 2020(the COVID year)in years,where GDP contracted by 1.6 and 3 percent,respectively.35.Previous growth accounting for Liberia undertaken by World Bank(2012;2018)offers credence to our result as
223、it also found similar patterns to those observed above.From 1970-2010,the World Bank(2012)study found that labour was the highest contributor to growth,followed by capital.On the other hand,the contribution of TFP is found to be the lowest and negative,with only one positive growth contribution out
224、of 4 episodes between 1970-2010(World Bank,2012).Yet,this World Bank study is not predicated on a rigorous econometric-based growth model approach.Instead,the authors used simple average factor shares values for their computation.36.In sum,when observed over the entire period,the result points to th
225、e relative marginal importance of removing the binding constraints,in order of importance,to total factor productivity(efficiency and technology,the effect of conflict,climate and external shocks),followed by capital accumulation and labour.Not only is the highest decline in the last two decades wit
226、nessed in the contribution of TFP,but it is also highly volatile.From the regression analysis and correlation test,as well as the growth accounting exercise above,it can be concluded that constraints related to total factor productivity and capital accumulation(including the latters negative value d
227、uring the conflict time and meagre and declining marginal return after the peace deal)are the significant binding constraints to growth in Liberia.Addressing these constraints will have the most important potential for high growth(with the highest shadow price).37.The deceleration of TFP to negative
228、 values over time(as well as its volatility and disproportionately high growth and low contribution to growth in some of the years)shows that TFP in Africa is not an indicator of technology or efficiency as that of the industrial countries.Because it is computed as a residual in Africa,it is instead
229、 dominated by the effect of,inter alia,external shocks(climate/whether condition and commodity price),statistical or political manipulation of growth figures,and the effect of conflict(AfDB,2021).In 2020,for instance,it became negative mainly because of the COVID-19 effect-not technology or efficien
230、cy.38.Concerns such as this(what does TFP indicate?)could be addressed by taking the above analysis further by examining other sources of growth from the supply side by examining the effect of sectoral growth,changes in productivity and structural transformation,which is done next.This helps to unpa
231、ck some of the factors behind the pattern of TFPs contribution observed above.This aims to further identify the most significant binding constraints to the accumulation and productivity challenges in this sub-section.Following this,the source of growth will also be examined from the demand side to c
232、omplete the investigation.332.2 Sectoral Source of Growth,Productivity and Structural Change 2.2.1.Sectoral Sources of Growth and their Binding Constraints39.One of the limitations of the growth accounting exercise undertaken so far is that it does not provide details about supply-side development,s
233、ectoral productivity,and dynamic interaction among sectors and the contribution of all these to growth.Analysis of sectoral sources of growth could shed light on this issue.The study of sectoral sources of growth in Liberia in the last two decades(2000-2021),for which we have adequate data,reveals t
234、he major points summarized below(Figure 2.5a).40.First,growth was driven by agriculture in the first decade that began in 2000.This changes in the second decade(2010-2021),when the growth of the service sector took over the prominent role of agriculture.Thus,the contribution of the service sectors g
235、rowth to GDP growth became 37 to 48 percent in the last decade(2011-2021),growing from the lowest contribution it had in 2001,which was 17.4 percent and 26.4 percent in 2010,when it was the highest in that decade.In tandem with this development,the contribution of the agricultural sector growth to G
236、DP growth has declined from the highest share it registered in 2001,57 percent,to the lowest contribution of 24 percent recorded in 2015 and 2016.However,this has recently increased to 31 percent in 2020 and 2021(Figure 2.5a).41.In addition to these two dominant sectors,the industrial sector has als
237、o contributed to growth at a rate comparable to that of the agriculture sector,especially since 2013(Figure 2.5a).Within the industrial sector,manufacturing in the first decade(2001-2010)and the Mining and Panning sub-sector in the last decade(2011-2021)were also significant contributors to GDP grow
238、th in Liberia,with a combined contributing share that ranges from the lowest rate of 22 percent(observed in 2010 and 2011)to 32 percent observed in 2009 and 2021.The manufacturing sector is usually considered the potentially dynamic sector for growth and employment creation.Unfortunately,the manufac
239、turing sectors contribution to growth declined significantly in the second decade of the last twenty years.Thus,its contribution to GDP growth had remained below 10 percent since 2010.This shows a significant decline from that of the previous decade,where it contributed from 17 to 24 percent between
240、 2001-2010.This signifies a clear deindustrialization trend,a sign of low technology,capital and human capital that also led to the concentration of the labour force in the low-productivity service section,which is common across the continent.(Figure 2.5a).In contrast,the growth contribution of the
241、Mining and Panning sub-sector emerged as crucial in the last decade,especially since 2010.Its contribution was almost none before 2010(Figure 2.5a).In the last decade,the contribution of this Mining and Panning sub-sector to GDP growth rose from the lowest share of 1.6 percent in 2010 to the highest
242、 percentage of 17 percent in 2021(Figure 2.5a).Iron ore,diamond and gold extraction are primary mineral resource sub-sectors contributing to this GDP growth share.34Figure 2.5a Sectoral Contribution to Liberias GDP growth(2001-2021)Source:Authors computation based on AfDB data42.Withing the service
243、sector,the contribution to the overall GDP growth in the last decade is dominated by the contribution of the growth of the public administration and defence sub-sector,which accounted for 34 to 42 percent of the service sectors growth in the last twenty years.This is followed by the contribution of
244、the growth in the Transportation and Communication sub-sector,which is closely followed by the Trade and Hotel sub-sector(Figure 2.5a).The rest of the service sectors contribution is widely distributed across many sub-sectors collected under the title other services”which became significant only in
245、the last decade,accounting for about 17 percent of the service sectors growth between 2013-2019(Table 2.5b).35Figure 2.5b Growth Contribution of Sub-sectors to the three main sectors(2019)Source:Authors computation from AfDB,202043.Growth in agriculture is the second important source of growth in Li
246、beria,as noted.Within the agricultural sector,growth in the production of food crops(cassava,rice and others)is the most significant driver of agricultural growth,accounting for nearly half(45 percent)of the sectors growth in 2012-2022(Figure 2.5b).This is followed by the growth of forestry products
247、 and exportable commercial crops(rubber,cocoa,coffee,and oil palm)(Figure 2.5b).50AgricultureServicesIndustry4540353025201510Export CropsFood CropsForestryOthersMining and quarryingManufacturingConstructionElectricity,gas&water50100%40.241.241421833.833.833.73434.715.725.723.82523.130.528.290%80%70%
248、60%50%40%30%20%10%0%2007Trade&HotelsTransport&CommunicationsPublic administration&defenceOthers Services2008200920000605040302020002020208200920000173644.Within the industrial sec
249、tor,the manufacturing and the electricity,gas and water sub-sectors were equally important in their contribution to the sectors growth,contributing about 30 percent each between 2007-2022.This was followed by the contribution of the mining and quarrying sub-sector,accounting for about 20 percent of
250、the industrial sectors growth,the construction sub-sector accounted the least(about 15 percent)(Table 2.5b).45.From the discussion thus far,we observe variation in the growth effect of sectors and sub-sectors to GDP growth over time.Generally,a change in the contribution of a sector(or a sub-sector)
251、to growth is the result of the change in productivity in the sector in question,as well as the movement of labour from one sub-sector to another,with varying levels of labour productivity or both.Besides,volatility in the growth contribution of some sectors and the sub-sectors also indicates problem
252、s in handling external shocks,as well as problems of growth sustainability and resilience that require the attention of policymakers.The changing pattern of sectoral and sub-sectoral growth in Liberia also points at the need to examine what has helped or constrained the expansion or otherwise of a s
253、ector or sub-sector.This,in turn,is related to the condition of productivity in each sector/sub-sector and the possibility of a shift of labour from low-productivity sectors and sub-sectors towards high-productivity sectors and sub-sectors structural change.The major driving force for this pattern(o
254、f the service sector taking over the agricultural sector)is the condition in agriculture that remained subsistence and low productive,as human and physical capital investment is limited.Neither was the sector modernized,yet,it employs about 43 of the labour force.This condition,combined with urbaniz
255、ation and rural-urban migration,means the service sector(including the informal sector in Monrovia)is increasingly absorbing the labour force.In addition,the service sector grew,driven by other services(education,health)that received increasing spending through significant external finance after the
256、 peace agreement.The hospitality and financial(including digital)sub-sectors also grew following the peace agreement,which led to the relative importance of the service sector.In sum,this structural change is one of the sources of growth of Liberia.Thus,examining the different dimensions of sectoral
257、 productivity and structural change(or its absence)in the last two decades helps to identify Liberias binding constraints to growth.The evidence on this is examined next.2.2.2.Productivity and Structural Change46.Compared to reference countries selected for benchmarking,the labour productivity in Li
258、beria is one of the lowest in the West Africa region,both in the agricultural(the lowest)and the service sectors(being better than Togo and marginally to that of Sierra Leone)(Figure 2.5c).Liberias level of productivity in these two sectors is below half the level in Senegal,the best performer among
259、 the peer countries selected.Among the three sectors,labour productivity in the industrial sector is relatively better,being the third highest among its peers,though still far below the level in Senegal(Table 2.5c).This shows the potential for high growth if the binding constraint in all sectors,par
260、ticularly the agricultural and service sectors,are addressed.(Figure 2.5c).37Figure 2.5c Sectoral Labor Productivity in Liberia(2019,in USD at 2015 constant price)Source:Authors computation based on WDI,World Bank data(2022)47.To get more insight into this general picture,the evolution of labour pro
261、ductivity over the last two decades,both at general and sectoral/sub-sectoral levels,is examined further in this section.This is done by decomposing these sectoral productivities into their different components.However,before proceeding to such analysis,it is worth pointing out that this analysis ha
262、s a limitation because it relied on labour productivity.This is because capital stock data is generally hard to come by in many developing countries,including Liberia.Therefore,this study has used an ICOR-based approximation of capital stock in Liberia,at least,to gauge the possible return to invest
263、ment by circumventing the capital stock data problem.48.Due to a lack of capital stock data both from national and international sources,the productivity and structural change analysis in this section is based on an in-depth examination of labour productivity and its changing trends in Liberia in th
264、e last two decades.This is done using equation 13.1Where:is the growth rate of labour productivity of sector i;is the growth rate of the share of sector i in total employment and is a weight given by the share of the sector i in total GDP.Zi is the sectoral(labour)productivity ratio to national(labo
265、ur)productivity.49.The first part of the equation 1 measures the contribution of productivity growth of each sector to total or national productivity growth referred to sometimes as the within sector effect or intra-effect.The second term shows the contribution of the reallocation of labour(level ef
266、fect)from the low-productivity sector to the high-productivity sector to the 12 00010 0008 0009 8441 5621 2459062 8142 1181 3642 9812 3272 9691 3141 6852 2351 8591 7675 0771 7521 0556 0004 0002 0000Agriculture,$/personGambiaGuinea-BissauLiberiaSenegalSierra LeoneTogoIndustry,incl construction,$/pers
267、onService,$/person3 The literature about decomposition of productivity shows various formulas(see for a recent review).This report employed what is called the“standard”formula due to its simplicity of interpretation and data requirement(see see de Avillez,2012;Dugmagan,2012 for a discussion of diffe
268、rent approaches).38aggregate productivity growth sometimes referred to as the level or the between sectors effect or re-allocation effect.The national productivity of a country can increase even if there is no growth in sectoral productivity simply by reallocation of labour from low to high-producti
269、vity sectors.Thus,this second term captures this effect.The final term,which could also be computed as residual,is a proxy to measure the contribution of the re-allocation of labour from low productivity to high productivity growth sectors.It captures the growth interaction effect.It will be positiv
270、e either when labour has moved towards a sector with positive labour productivity growth or when it has moved away from a sector with negative labour productivity growth.Its magnitude also depends on the ratio between the sectors labour productivity and the aggregate labour productivity levels,its w
271、eight given by z.This last effect is sometimes called the dynamic re-allocation effect(see de Avillez,2012).The last two parts of equation 1 show the effect of structural change on productivity growth.The result of this computation for Liberia,using data for the last two decades,is given in Table 2.
272、3.50.Table 2.3 shows that productivity growth both at the macro(national)level and across major sectors had been extremely low and volatile over the last twenty years.At the national level,labour productivity is negative between 2001-2019(Table 2.3).Productivity is the highest in the industrial sect
273、or,with an average period growth of 3.43,primarily driven by the manufacturing sectors productivity growth(at 3.8 percent)during the two decades under analysis.This is followed by the agriculture sector(0.70 percent).The service sector had the lowest growth rate(-1.11 percent)among all sectors(Table
274、 2.3).As can be read from Table 2.3,the worst within productivity growth is observed during the conflict period,before the 2005 peace agreement and election.During this period(2001-2005),national productivity declined by a staggering 7.5 percent,with negative growth across all sectors except the ind
275、ustrial sector(especially the manufacturing and construction sector),which saw dramatic positive growth of 12 percent).The within productivity growth is negative in the industrial sector,including manufacturing,mining,construction and utilities.The sub-sector trade in services also had a negative gr
276、owth rate during the entire period(Table 2.3).51.Notwithstanding the positive picture in agriculture and national productivity growth,agricultures within productivity growth has declined from about 5 percent in 2000-2004 by more than 50 percent to 2 percent in 2015-2018.Given the average population
277、growth of about 2.6 percent during the same period,this shows a negative per capita output growth in the agricultural sector.The picture at the national level is similar to this picture in the agricultural sector(Table 2.3).Following the revival of productivity growth during 2006-2010(the peace and
278、democratic period),the within productivity has generally declined across sectors and over time.During this time,it appears that the national productivity growth is generally governed by the trend of productivity in the agricultural and service sectors(Table 2.3).3 The literature about decomposition
279、of productivity shows various formulas(see for a recent review).This report employed what is called the“standard”formula due to its simplicity of interpretation and data requirement(see see de Avillez,2012;Dugmagan,2012 for a discussion of different approaches).39Table 2.3 Decomposition of Productiv
280、ity growth in Liberia(2001-2019)Source:Own computation from AfDB data(2022)value-added and ILO(2021)for employment data Note:M+M refers to mining and manufacturing;C+U to construction and Utilities(power and water)52.The contribution of the static re-allocation effect(the between effect)to growth ha
281、d been,on average positive only in the service sectors and sub-sectors during the whole period,this being negative both in the agricultural and industrial sectors(Table 2.3).In the latter two sectors,this allocation effect was positive only from 2001-2005.This negative effect is the highest for the
282、service and agricultural sectors(at-0.65 percent),followed by the industrial sector at-0.24 percent(Table 2.3).The dynamic re-allocation effect on productivity growth is also negative across sectors,except in the service sector(excluding the transport service sub-sector)(Table 2.3).The latter indica
283、tes the absence of a labour movement either to sectors with high productivity growth or away from the sectors with low productivity growth in the agricultural and industrial sectors.53.Several policy lessons can be drawn from these findings.First,halting the declining trend of per capita output and
284、productivity growth in the agricultural sector by addressing major binding constraints will significantly contribute to national productivity growth,and hence growth,in Liberia.Thus,it is imperative to identify major constraints in this sector for a high impact on growth in Liberia.This finding is s
285、imilar to the World Banks(2013)findings about low agricultural productivity,which also led to the declining contribution of the sector to(All in%)WithinAgricultureIndustry(M+M+C+U)ManufacturingConstructionServiceTrade ServicesOther servicesNational Labour Productivity Growth2001-05-2.9212.0813.652.8
286、5-3.78-3.92-0.72-7.452006-104.910.510.44-0.010.261.01-0.105.352011-150.960.280.300.060.45-0.370.120.472016-19-0.370.190.100.07-1.42-0.85-0.71-1.422001-190.703.433.810.78-1.11-1.04-0.33-1.04Between AgricultureInd(M+M+C+U)ManufacturingConstructionServiceTrade servicesTransport servicesPublicservicesOt
287、her services2001-050.400.04-0.010.06-0.09-0.010.02-0.10-0.212006-10-1.09-0.09-0.130.030.230.050.050.150.272011-15-1.59-0.56-0.35-0.080.350.050.060.290.502016-19-0.22-0.38-0.20-0.060.100.010.020.080.142001-19-0.65-0.24-0.17-0.010.150.030.040.100.18DynamicAgricultureIndustryManufacturingConstructionSe
288、rvicesTrade servicesTransport servicesPublicservicesOther services2001-05-0.540.78-0.021.530.190.28-0.5313.970.292006-10-0.51-0.08-0.25-0.010.010.02-0.03-5.80-0.042011-15-0.29-0.42-0.99-0.280.040.00-0.04-3.790.112016-19-0.07-0.33-0.58-0.47-0.020.00-0.05-1.40-0.082001-19-0.3700.003-0.4550.2270.0600.0
289、77-0.1710.8600.07740national growth.Given that agriculture accounts for 42 percent of employment(2019),a positive development in the sector will significantly affect the national growth and welfare of the majority of the Liberian population(see also WB,2013).54.Second,although static re-allocation o
290、f labour to the service sector was one of the significant factors to productivity growth and economic growth in Liberia in the past,as can be learned from the between effect,the labour is moving to this sector and sub-sectors that are generally characterized by negative within sector productivity(th
291、e worst of this for the sector being-1.11 percent growth,followed by trade services at-01.04 percent).This result implies that raising sectoral productivity both in the service sector(and its sub-sectors),by addressing their binding constraint is crucial to have a high impact on growth.55.Finally,th
292、e finding also shows that lately(since 2005),labour is not moving either to sectors with rising productivity or leaves sectors with low or negative growth in productivity(indicating a lack of dynamic productivity),especially in the agricultural,manufacturing and transport sectors,while this is not t
293、he case in the rest of the sectors given in Table 2.3.Effecting a structural transformation that changes this observed pattern is also crucial to raise national productivity and economic growth in Liberia.2.3 The Demand Side Sources of Growth56.On the demand side,the economic performance since 2000
294、is driven mainly by private consumption.During 2000-2015,private consumption accounted for 93 to 140 percent of the source of GDP growth on the demand side.However,this has sharply declined after this period,to an average annual contribution of 70 percent for the 2016-2021(Table 2.2a).Gross capital
295、formation ranks second as a source of growth from the demand side,contributing about 20 percent to GDP growth between 2000-2009 and 38 percent between 2010-2014.This sharply increased to 61 in 2015,although it declined to 51 percent in 2016.It failed further and stabilized at an average annual contr
296、ibution of 36.6 percent to GDP growth between 2017-2021.Though it fluctuated significantly,this pattern shows that investment demand was Liberias second important source of GDP growth.This result also shows that enhancing the effectiveness of investment is essential to diversify sources of growth fr
297、om the demand side away from private consumption,which is the dominant contributor to growth.Next to investment,government consumption also contributed to GDP growth from the demand side.Thus,it contributed 12 to 17 percent per annum in the first half-decade of the 2000s;and between 31 to 54 percent
298、 after this period(Table 2.2a).4157.The persistent trade deficit since 2000,as for most African countries that are dependent on the export of few primary commodities and significant imports,contributed negatively to Liberias growth on the demand side throughout the period under analysis(Table 2.2a).
299、This negative contribution was moderate at 30 percent between 2000-2005,but became significantly negative in the subsequent years,reaching the highest negative contribution of 90 percent in 2015,easing to negative 60 percent in 2016,before stabilizing at an average annual contribution of negative 30
300、 percent between 2017-2021.This trade deficit is attributed to the nature of the countrys exports and imports,where the latter was two to four times that of the former during this period(Table 2.2a).The latter is also detailed in Table 2.2b and discussed in the following sub-section.Table 2.2a Deman
301、d Side Sources of Growth in Liberia(2000-2022)Source:Authors computation from African Development Bank(AfDB)data,2022.2.3.1 Structural Trade Deficit and Its Negative Contribution to Growth58.The negative effect of net exports on growth on the demand side described above reflects Liberias external se
302、ctor structural problems.The sector was characterized by overdependence on export revenue from a few primary commodities whose prices and volumes are characterized by significant volatility and deterioration of the countrys terms of trade during the period under analysis.59.Like most countries in Su
303、b-Saharan Africa,Liberia is a primary commodity-dependent country with a significant concentration of exports on a few commodities:minerals(iron-ore and gold),rubber and a few agricultural and forestry products.The combined share of these items in total export was over 90 percent since 2014 and 75 t
304、o 87 percent before that(Table 2b).Before 2010,the export structure was dominated by non-mineral primary commodities,mainly rubber export.But from 2012 onwards,minerals(iron ore,diamond and gold)export took over other primary commodity exports.The gradual shift towards mineral exports after 2012 is
305、attributed to improved infrastructure,gradual -2001920202021Average GDP growth-5.720.57.00.01-1.62.51.24-1.4-2.93.31Contribution to growth Final private consumption expenditure 102.1139.591.292.977.972.664.766.566.769.1Gross capital formation 21.020.537.660.6
306、50.838.240.536.333.334.9General government final consumption expenditure 12.216.834.953.844.836.533.135.630.330.6Net export-29.7-74.6-55.9-90.0-58.8-37.3-29.9-27.2-24.1-29.6Total00100100Memo(contribution of)Exports of goods&services 42.340.032.232.626.823.026.027.523.923.1 Impo
307、rts of goods&services-72.0-114.5-88.1-122.6-85.6-60.3-55.9-54.7-47.9-52.742recovery of the extractive sector,multi-billion mining investment(CBL,2012),and the return to peace attained during the period.In addition to this product concentration,Liberia has a strong concentration of destination of exp
308、ort(Switzerland,China,USA and UAE)and source countries for its imports(China,India,USA,Cote DIvoire,UAE,other Middle East countries)(CBL,2021;Table 2.3).60.Liberias exports are characterized by significant volatility of prices and volume growth(table 2.2b and figure 2.2).In 2011-2018,rubber export s
309、uffered severe negative annual unit price growth,but bounced back to positive growth after that.However,annual unit price growth was generally positive for minerals exports since 2017(Table 2b).However,the global prices of Liberias main exports were widely volatile,its growth swinging between positi
310、ve and negative values in the last five decades,1965-2021(Figure 2.2).Table 2.2b Export demand as a source of growth(2000-2019)Source:Authors computation based on Central Bank of Liberia(CBL),2021;2020.Note:*Minerals is the sum of iron ore and gold,a small(below 4%)amount of diamond.Others is primar
311、ily agricultural products such as coffee,palm oil and other re-exports.e=estimatesRubberMinerals*Rubber,minerals(combined)Other exports&re-exports(share in total%)Total in millions of$YearShare in total export(%)Unit value(growth)Share in total export(%)Unit value(growth)201239.8-21.835.1184.374.924
312、.1444.4201323.8-24.963.0125.986.813.2558.9201417.5-26.275.620.593.16.9560.8201521.6-37.768.9-54.090.69.4283.3201620.0-8.569.2-1.089.29.7279.3201721.537.769.328.590.98.1358.2201813.2-11.177.962.291.18.9516.96201915.74.476.421.692.17.9542.9202013.55.581.622,595.14.9607.72021e12.519.780.025.192.57.5878
313、.543Figure 2.2 Global Price Volatility of Major Export Commodities of Liberia(1965-2020)Source:Authors computation based on World Bank Global Commodity Price data,2022.61.Similar to prices,the volume growth of both exports and imports also shows significant volatility.For example,for 2001-2022,the v
314、olume growth of imports was generally negative in 12 of the 21 years,while the volume of exports exhibited a positive growth rate in more than half of the years(Figure 2.3).Although export volume growth has been positive since 2011 and peaked at 119 percent in 2013,it decelerated sharply to-8,5 and-
315、14.6 percent growth in 2014 and 2016,respectively.Import volume growth rate also dropped sharply to negative 15 percent and 28 percent in 2016 and 2017,respectively,from a peak of 68 percent in 2014.Thus,GDP growth was generally propelled during this period relatively more by the growth of exports t
316、han by restraint in imports.The combined effect of the decline in the growth of exports and the rise of imports in 2014 resulted in a sharp deterioration of the current account to negative 62 percent of GDP in 2014,before beginning to recover thereafter,but remains negative and significant(Figure 2.
317、3).120%Change GOLD%Change IRONORE%Change RUBER100806040-40-600502005200-20044Figure 2.3 Current Account Balance and Growth of Imports and Exports of Liberia(2001-2022)Source:Authors computation based on AfDB data(CA balance on the right axis)62.For the per
318、iod 2019-2021,Liberias imports were dominated by food and live animals and machinery and transport equipment,which accounted for 39 and 24.4 percent of the total imports,respectively,and together accounted for 63 percent of the total imports.Imports of mineral,fuel and lubricants followed at 36 perc
319、ent of which petroleum products alone accounted for 79 percent Other(CBL,2021).This import structure shows the inelastic nature of imports,given that most imports are necessities(such as food and fuel)and items needed for investment(such as machinery).As a share of GDP,these imports of goods were ab
320、out 34 percent,while exports of goods stood at 21 percent for 2019-2021.This gap widens when service exports and imports are considered.Using the AfDB(2022)data for 2004-2021,imports of goods and services were,on average,about 3.2 times that of exports of goods and services per annum,but declined to
321、 2.3 in the last five years(2017-2021).63.This pattern of imports and exports of Liberia,combined with the evolution of the global price of its major exports and imports,has led to the deterioration of the countrys terms of trade(TOT)deteriorate in the last two decades(Figure 2.4).Over the period,Li
322、berias TOT deteriorated at an average annual rate of 3 percent,while TOTs growth decelerated at an average rate of 12 percent per annum.140,0120,0100,080,060,040,020,0-20,0-40,0-60,0-80,0Exports Volume Growth(Goods)Current Account Balance,%of GDPImports Volume Growth(Goods)-70,0-60,0-50,0-40,0-30,0-
323、20,0-20,8-62,2-9,7-3,8-10,00,02000420052006200720082009200000220,045Figure 2.4 Terms of Trade(ToT)and its Growth(RHS)in Liberia(2002-2018)Source:Authors computation based on AfDB data.Note:The ToT for 2010 is an outlier with a value of 80,compar
324、ed to the period average of-0.3 percent and hence does not show the general pattern and is excluded from the graph as a result(replaced by the average value of adjacent values)64.When the poor export performance in terms of both volume and prices is combined with a high level of imports,and the term
325、s of deterioration are noted,it shows the countrys structural trade(and current account balance)deficit problem(Figure 2.3).This has,among others,resulted in a persistent negative contribution of net exports to growth from the demand side,as shown in Table 2.2a.In addition,Liberias exports and impor
326、ts show a significant concentration of destination and source countries,respectively.Concerning imports,based on CBL(2021)data for 2019-2021,imports primarily sourced from Asia(mainly India and China)accounting for 60 percent of imports,Africa(dominated by ECOWAS,mainly Cote dIvoire)follows at 20 pe
327、rcent,and Europe(primarily the Netherlands)at 13.6 percent.On the other hand,exports are destined mainly to Europe,accounting for 76.1 percent of total exports in the same period.North America and the Caribbean follow this at 18.1 percent and Asia at 9.4 percent.Africa had the most negligible share
328、of just 2.5 percent of Liberian exports,showing the limited use of the potential African market,such as AfCFTA(CBL,2021).This pattern shows the strong concentration of trade,which is a risk factor in the event of shock in these countries.These features of the external sector have implications for th
329、e countrys external sector and macroeconomic stability,a risk factor for investment discussed in detail in section four below.65.The pattern of exports and imports in the last two decades shows the challenge of a persistent trade balance deficit that needs to be addressed by raising traditional expo
330、rts and diversifying to non-traditional exports simultaneously.In small countries such as ln(y)=-0.0312x+5.29ln(y)=-0.127x+2.1-40,0-30,0-20,0-10,00,010,020,030,040,005002002200320042005200620072008200920001620172018Terms of Trade Growth46Liberia,relying on expanding
331、domestic demand(such as household consumption)has the unintended consequence of further aggravating the already high trade balance and balance of payment deficit.On the other hand,Liberia also needs to judiciously manage its imports to be compatible with its foreign exchange generation capacity,as c
332、an be read from the growth of its exports.Otherwise,if left unchecked,the trade balance deficit will exacerbate the debt burden,which reached about 48 percent of GDP in the last three years(2019-2021).The combined effect leads to a significant macroeconomic imbalance and risks to private economic ag
333、ents.This shows the vulnerability of Liberias growth to its external sector,discussed further in section four.In addition,the dependence on primary commodity exports and imports of manufacturers has led to the deterioration of the barter terms of trade in Liberia over the last two decades(Figure 2.4).The latter,in turn,is found to have a significant adverse effect on growth,as shown by the correla