rafmacalaba/datause-encoder-data huggingface dataset:
||4.7|Informal Sector Activities in Ghana|27-28|
|---|---|---|---|
|5.|Educ|ation and Earnings|29-36|
||5.1|Public and Private Sectors|31-32|
||5.2|Quality of Education|32-33|
||5.3|Family Background, Private-Public Choice and|33-34|
|||Returns to Education||
||5.4|Trends in Child Labor and Schooling in Ghana|34-36|
|6.|Rura|l-Urban Earnings Difference|36-49|
||6.1|The Pre-Crisis Economy|36-37|
||6.2|The Course of Rural-Urban Earnings Differences during the<br>Economic Decline|3840|
||6.3|The Rural-Urban Difference after the Recovery|40-44|
||6.4|Factors Affecting Rural-Urban Differences in Trends in<br>|4449|
|||Income and Poverty||
|||6.4.1 The Absorption of Labor|45-46|
|||6.4.2 The Formal-Informal Earnings Difference in Urban Ghana|46|
|||6.4.3 Income Growth and Poverty Reduction in the Rural|46-47|
|||Economy||
|||6.4.4 Absolute Levels of Poverty in the Rural and Urban|47-49|
|||Sectors and Labor Migration||
|7.|Conc|lusions and Recommendations|49-53|
||7.1|The Future of Labor Absorption in Ghana|49-53|
||7.2|An Agenda for Future Research|53|
|REF|ERENC|ES|54-55|
|App|endix 1||57-61|
|App|endix 2||62-65|
SOEs.<sup>10</sup> Many of these SOES are chronic loss-makers, resulting in a severe misallocation of credit. In addition, using a smaller sample than we do, Ayyagari, Demirguc-Kunt, and Maksimovic (2010) find that Chinese firms, state-owned or non-state, that report government help as instrumental in obtaining a bank loan do not show subsequent improvements in growth, reinvestment or productivity, unlike other recipients of bank loans.<sup>11</sup> By relying on institutions to identify firms facing financial constraints, our study is closest to Hoshi, Kashyap, and Scharfstein (1991) who classify Japanese firms by whether they belong to a business group (keiretsu) and find that group members have lower investment-cash flow sensitivities than other firms.

Another reason the FHP methodology works well in the Chinese context is that, due to China’s underdeveloped capital market (Gordon and Li, 2003), external finance for Chinese firms is largely limited to bank credit, making it easier to understand the trade-offs they make between internal funds and limited sources of external funds. In studies using U.S. data, sample firms tended to be large publicly traded firms. The debate there hinged on whether the lack of dividend payments (the FHP approach) was a more reliable a priori indicator of financial constraints than indicators based on qualitative information in their annual 10-K reports

> 10 See Brandt and Li 2003; Boyreau-Debray, 2003; Cull and Xu, 2003; Gordon and Li, 2003; Allen, Qian, and Qian, 2005; Boyreau-Debray and Wei, 2005; Bai et al. 2006; Li et al. 2008; Cull, Xu, and Zhu, 2009; and Gordon and Li, 2011.

> 11 At first blush, findings from Ayyagari, Demirguc-Kunt, and Maksimovic (ADKM) (2010) on the ineffectiveness of informal finance in spurring firm growth and productivity would appear to contradict those from Allen, Qian, and Qian (AQQ) (2005). However, the positive effects of informal finance on productivity growth and firm investment only emerge in the AQQ study when informal finance is defined to include internal financing. Thus, our findings regarding the high sensitivity of firm investment to internal finance for some firms are in line with those in AQQ. At the same time, our findings are also supportive of those in ADKM in that proxies for use of formal sources of external finance are also strongly associated with investment, especially within the sub-sample of non-state firms. The issue is that, because of the misallocation of credit toward government-owned and government-connected firms, many non-state firms do not receive sufficient bank credit to fund all profitable investment opportunities. This is reflected in the regressions below in the strong positive association between investment and internal cash flows for those non-state firms, even after including proxies for formal sources of external finance.

10
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Rubin, Donald B (1987) _Multiple imputation for nonresponse in surveys_ (New York: Wiley) Stata (2013) _Multiple-Imputation Reference Manual._ Stata Press

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# **I. INTRODUCTION**

Africa is abundant in natural resources and has great potential for agriculture. Agriculture and agribusiness currently generate nearly half the GDP of the region, or $313 billion of commodities and products every year. This is projected to increase to $1 trillion by 2030 (World Bank 2013). However, significant potential remains to be developed. Africa’s agriculture is still mostly small-scale subsistence farming, and the current yields are far below potential levels (e.g., World Bank 2012).

Despite recent fluctuations, international commodity prices driven up by strong global demand for food are still favorable to many African countries. For instance, Africa’s coffee and groundnuts prices nearly doubled in the 2000s (Figure 1). Tea and cotton prices also increased by 30-40 percent (World Bank 2013). In the last five years, coffee exports from East Africa nearly doubled in value terms (Figure 2). However, this is largely explained by the high commodity prices, not export quantities (Figure 3). Trade statistics show no clear evidence of a sharp supply response in Africa. As a result, Africa’s presence in the global food market has been declining over the last decades.<sup>1</sup> Farmers’ shift toward cash and export crops seems to be particularly slow in Africa. A variety of constraints have been discussed in the literature. In Africa, for instance, farmers have little access to quality inputs and new technology. Irrigation and fertilizer are critical inputs for agriculture (e.g., Gyimah-Brempong, 1987; Bravo-Ortega and Lederman, 2004), often found to be lacking. In Zambia, timely fertilizer supply increased maize yields by 11 percent on average (Xu et al., 2009). Irrigation availability nearly doubled agricultural productivity in Mali (Dillon, 2011). In general, however, access to agricultural inputs in Africa is problematic for many agricultural producers.

> 1 Africa’s share of global agricultural exports declined from 7 percent in the 1970s to 2 percent in 2009 (World Bank 2013).
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58
|**4**<br>**Co**|**mputational details**|**18**|
|---|---|---|
|4.1|Truncated Gauss-Hermite approximation. . . . . . . . . . . . . .|. . . . . . . . . . . . .<br>18|
|4.2|Solving the model<br>. . . . . . . . . . . . . . . . . . . . . . . . . .|. . . . . . . . . . . . .<br>19|

2
intra-household level information on employment and assets,”<sup>2</sup> the LSMS+ program has coordinated with country national statistical offices to include self-reported, individual-level modules on asset ownership and rights, as well as labor, as part of ongoing, multi-topic, nationally-representative surveys. The LSMS+ modules follow 2019 United Nations guidelines for producing statistics on asset ownership from a gender perspective, prepared under the Evidence and Data for Gender Equality (EDGE) project.<sup>3</sup> With an emphasis on self-reported data to fully capture intra-household gender inequalities in asset ownership, LSMS+ aims to address widespread data gaps on individual wealth and improve the accuracy in estimates of wealth. This is in contrast to more common survey approaches that — when data on wealth are collected — tend to either collect this information at the household level, or by one respondent per household who answers for others (see Kilic, Moylan and Koolwal, 2021 for a discussion).

In this paper, we use publicly available data from LSMS+ supported national surveys that were conducted in Malawi (2016 Integrated Household Panel Survey), Tanzania (2019/20 National Panel Survey), Ethiopia (2018/19 Ethiopia Socioeconomic Survey), and Cambodia (2019 LSMS+ Survey).<sup>4</sup> Table 1 presents the main features of these surveys. Individual wealth is constructed in our analysis using data on individuals’ selfreported ownership and valuation of different assets in the LSMS+ surveys. The aforementioned UN guidelines recommend that countries collect information, at a minimum, on the principal dwelling, 2 World Bank, 2016.

3 See UN (2019). EDGE was launched in 2013 as part of a collaboration between the US Government, the United Nations Statistics Division and UN Women, along with key regional and international agencies including the OECD and the World Bank. The UNEDGE guidelines were also informed by country pilots including the Methodological Experiment on Measuring Asset Ownership from a Gender Perspective (MEXA) in Uganda (Kilic and Moylan, 2016).

> 4 The anonymized unit-record data from all surveys are publicly available on the World Bank Microdata website: <u>https://microdata.worldbank.org/index.php/home</u>

6
Table A9: IV regression: The effect of migration on land tenure arrangements, using the residual approach: Acreage, No controls

||(1)<br>fxed rent|(2)<br>fxed (money)|(3)<br>fxed (crop)|(4)<br>sharecropping|(5)<br>relatives|(6)<br>contract length|(7)<br>written contract|
|---|---|---|---|---|---|---|---|
|migration|0.959**|0.982***|-0.0228|-0.823*|-0.0471|0.457|0.445*|
||(0.417)|(0.350)|(0.287)|(0.438)|(0.316)|(0.404)|(0.266)|
|2012 year|-6.611**|-2.691|-3.919*|-2.721|8.885***|20.05***|1.511|
||(3.228)|(2.901)|(2.253)|(3.169)|(2.110)|(2.980)|(2.051)|
|Constant|-14.52|-33.45|18.93|94.52***|7.859|8.357|-16.55|
||(26.01)|(21.77)|(17.81)|(27.39)|(19.71)|(25.25)|(16.62)|
|Observations|927|927|927|927|927|927|927|

Note: This table uses the residual shift-share instrumental variable regression to present the relation between the percentage of rented-in acreage under various terms and the number of high-skilled male out-migrants between the ages of 20-64 years (as a percentage of the total male out-migrants between the ages of 20-64 years). The dependent variable is as a percentage of acreage of rented in land. Robust standard errors. *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1.
Tables 2 and 3 present a result from the growth accounting that underlies TFP estimation – Figure 3 presents the full growth accounting for the fastest growing countries measured by GDP. These tables isolate the effects of natural resource growth – Table 2 presents countries where growth in natural resource extraction and harvest added more than 10% to GDP growth, while Table 3 presents countries where the decline of natural resource inputs decreased GDP growth by 1% or more. To be clear, Table 3 shows that (other things being equal) the GDP growth rate of Ukraine would have been 2.7% on average over 1996-2014 if natural resource inputs had been constant.

# **Table 2. Countries where growth in natural capital inputs added more than 10% to GDP** **<u>growth over 1996-2014</u>**

||GDP<br>growth<br>rate|Natural<br>capital<br>contribution|
|---|---|---|
|Sierra Leone|5.8%|37.5%|
|Niger|4.5%|25.6%|
|Iraq|7.4%|22.7%|
|Togo|3.3%|17.0%|
|Azerbaijan|10.1%|16.9%|
|Chad|7.4%|16.6%|
|Kazakhstan|6.2%|15.0%|
|Suriname|3.7%|14.3%|
|Lao PDR|7.1%|14.0%|
|Mongolia|6.7%|13.9%|
|Bolivia|4.1%|12.1%|
|Burundi|2.3%|10.9%|
|Guinea|3.0%|10.5%|

A note on interpretation: The 37.5% contribution that natural capital growth makes to the GDP growth rate of Sierra Leone (for example) amounts to 2.2% of the total 5.8% GDP growth rate.

18
```
- 26 -
``` ``` Sustaining growth thus becomes something of a ‘high-wire’ act – continual crisis management, endlessly putting out fires in an environment which to the casual observer seems quite dysfunctional, but nonetheless defies the odds by sustaining continuing dynamism.
``` ``` Note that the ‘just enough governance’ sequence should not be construed as a relatively painless (if nerve-wracking) development strategy. For one thing, there are multiple countries where the economic environment is too dysfunctional, and institutions are too weak, for incremental reforms to be enough to kickstart growth. For another, not all binding constraints can necessarily be eased through incremental measures. Moreover, as growth proceeds, society changes profoundly – with new pressures, and new opportunities building up. At some point channel 3 (identical in Figures 1 and 3) is likely to become dominant – laying the stage for a non-incremental transformation of political institutions.
``` ``` Experiences and challenges. The ‘Bangladesh paradox’ offers a vivid example of the relevance of a ‘just enough governance’ ``` ``` development strategy. Over the past decade, Bangladesh has made major gains in development performance. In the three decades since the country’s independence in the early 1970s, per capita income has more than doubled; the poverty rate has fallen from 70 to 40 percent; child immunization rates have risen from negligible levels to close to 80 peercent; life expectancy at birth has gone from 45 to 63 years. (World Bank, 2006) Yet over the same period, the country also rated consistently as among the most corrupt in the world: Other governance indicators also rated poorly. Key to Bangladesh’s paradoxical ``` ``` achievement were a series of ‘just enough’ development reforms: good macro-economic management, targeted trade policy reforms which provided just enough openness to enable a take-off of the garment export sector ```
- 56 -

# BBLIOGRAPHY

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- Prud'homme, Remy. "Decenrization of Expenditures or Taxes: The Case of France." ID R.J. Bennett (ed.), _Decentralization, Local Governments and Markets._ Oxford: Clarndon Press, 1990.

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- Thirsk, Wayne Ri "Political Sensitivity versus Economic Sensibility: A Tale of Two Property Taxes.? In Wayne R. Thirsk and John Whalley ed., **_Tax_** _Policy Options in_ **_te 1980's,_** Canadian Tax Paper No. 66. Toronto, Canada: Canadian Tax Foundation, 1982, pp. 3S4-401.

- World Bank, _Infraosruefr Develpment._ World Development Report, 1994. Washington, D.C., 1994.
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forward integration, albeit higher on forward participation in the global sample. On the contrary, distance to major manufacturing hubs has a strong positive effect on both backward and forward integration in SSA. This means that hubs that are relatively farther away from SSA tend to trade more in manufacturing GVCs than those that are closer to the region. This is not very surprising for two main reasons. First, is China’s increasing presence in the African continent despite not being the closest major manufacturing hub. Apart from China being one of the continent’s major trading partners for the past decade, SSA countries are increasingly diversifying their export partners toward the BRIC and other emerging economies which are far from the closest manufacturing hubs (i.e. Germany). Second, the strong positive effect of distance on backward and forward GVC participation in SSA can be explained by South Africa’s presence in the SSA sample. This is because South Africa has the highest rate of integration in global value chains despite being the farthest country from the three major manufacturing hubs.

# **VI. Concluding remarks and policy recommendations**

This study assesses the role of human capital and natural resource endowment in SSA participation in manufacturing GVCs. We looked at the effects for both backward (FVA) and forward (DVX) participations as well as the overall GVC participation ratio. Fixed effects panel regressions with robust standard errors are estimated for 23 SSA countries and results are compared with a global sample of 115 countries, covering 19 manufacturing subsectors. Because of the lack of skilled/unskilled labor data for most SSA countries, we generated skilled/unskilled labor content in export using the labor content of exports (LACEX) methodology developed by Cali et al. (2016). We mapped the skilled data set defined for 57 sectors from the input-output GTAP table with the GVCs data derived from UNCTAD-Eora GVC Database which has 25 sectors. We focus on the impacts of skilled/unskilled labor contribution, migration and initial human capital endowment on forward and backward GVC participations. To our knowledge, this study is the first in the literature to assess the role of skilled and unskilled labor, net inflows of skilled/unskilled migrant workers, and the human capital index in GVCs integration. Importantly, this is the first study that focuses on SSA countries where skills related data are often very difficult to collect.

30