rafmacalaba/datause-encoder-data huggingface dataset:
# **I. Recent Evolution of the Private Equity and Venture Capital Industry**

# **A. Industry Overview: Kenya in Context**

Less than a decade ago, the fledgling commercial private equity industry<sup>2</sup> in Africa was largely confined to and based out of Southern Africa. From 2008 to 2010, nearly 60 percent of investment in Sub-Saharan Africa was destined for South Africa, with regional hubs like Nigeria and Kenya trailing far behind in terms of both market share and mind share. Then, aided by continent-wide resilience in the aftermath of the 2008 global financial crisis, the region’s growth story attracted an influx of private equity investors to Africa. These new entrants looked beyond the increasingly crowded South African market to explore other subregions and countries on the continent (Figure 1).

**Figure 1: Distribution of Sub-Saharan Africa PE Investment by Value**

<!-- Start of picture text --> % Total Investment: 2008-10 % Total Investment: 2013-15<br>Other, 20% South Africa<br>28%<br>Other<br>37%<br>Kenya, 8%<br>South Africa,<br>57%<br>Nigeria, 15% Kenya Nigeria<br>16% 19%<br><!-- End of picture text -->

# _Source: EMPEA_

Within this context, East Africa, and particularly Kenya, has become an increasingly important destination for private equity investors. Beyond offering relative regulatory stability, Kenya has long been known for its private sector-led economy, and for the sophistication of the business environment, both in an absolute sense, but particularly relative to the other economies of East Africa. In addition, Kenya boasts a strong entrepreneurial class and benefits from a good supply of human capital, both local and international. Thus, when private equity interest migrated from South Africa into the rest of the continent, Kenya captured a disproportionate share of the activity, both in terms of deal flow and funds. Although it is just the third largest country in East Africa by population, and the seventh largest economy in Africa by nominal GDP, Kenya’s standing in the alternative investment industry in Africa is notable. The country now ranks third behind South Africa and Nigeria in terms of private equity transactions in SSA: PE funds invested more than US$750 million across nearly 50 deals based in Kenya from 2013-2015.

> 2 Note, for the purposes of this report, private equity, when referred to and discussed as an industry, is inclusive of venture capital as well.

3
impact of the economic crisis in 2009. In Section 4, we summarize the main results and conclude.

# **2. Methodology**

The methodology used in this paper builds on Senauer and Sur (2001) and consists of three broad stages which are detailed below. The first part is the estimation of the calorie-income relationship, or the calorie Engel curve using data on per capita income and per capita calorie consumption available for a group of 83 low and middle-income countries. The second component uses country-specific income distribution data to construct a cumulative density function (cdf) of per capita income for all countries in our sample. These two steps allow us to estimate, at any given level of food price and any given level and distribution of income, the fraction of individuals unable to afford the minimum threshold caloric intake necessary to avoid undernourishment for every country in the sample. The third stage involves aggregating these country estimates to create regional baseline undernourishment numbers and simulating different food price and growth scenarios to assess the impact on undernourishment. This section describes this methodology in greater detail.

# **2.1     The Calorie-Income Relationship**

The literature points to a wide variety of estimates for the income elasticity of calories ranging from close to 0 to close to unity. Bouis and Haddad (1992) arrive at estimates that range from 0.08 to 0.14 for the Philippines and conclude that though statistically significant, the magnitudes are too small for growth in income to lead to material improvements in nutritional status. Similarly, Behrman and Deolalikar (1987) use data from India and find the point estimate of this elasticity to be 0.37 but statistically indistinguishable from zero. Low or close to zero elasticity for the calorie-income relationship is also reported in Alderman (1993) and Strauss and Thomas (1995). Subramaniam and Deaton (1996), on the other hand, find this elasticity to be around 0.55 for the poorest households in rural Maharastra and around 0.40 for the better off households in the sample. As argued by Reutlinger and Selowsky (1976), Strauss and Thomas (1990) and Ravallion (1990) there seems to be a general agreement on the fact that there are
Table 3 Summary Statistics: Uganda National Household Survey Market Density and Village Controls

||Average|Std. Dev.|
|---|---|---|
|MARKET DENSITY|||
|Export crops|0.37|0.31|
|Food|0.76|0.24|
|DISTRICT CONTROLS<sup>1</sup>|||
|Distance to paved road|25.90|21.28|
|Access to credit|0.68|0.30|
|Access to improved seeds|0.58|0.28|
|Access to oxen|0.26|0.36|
|Access to oxen rental|0.21|0.31|
|Access to tractors|0.12|0.18|
|Access to extension services|0.38|0.24|
|Output market constraints|0.15|0.14|
|Input market constraints|0.16|0.12|
|Road constraints|0.05|0.08|
|Disease constraints|0.22|0.18|
|Security constraints|0.01|0.03|
|Land constraints|0.15|0.20|
|Credit constraints|0.04|0.08|
|Land fertility constraints|0.08|0.09|
|Access to veterinary services|0.28|0.26|
|Land confict|0.13|0.12|
|Land community|0.08|0.23|
|Access to primary school|0.49|0.21|
|Free medicine|0.43|0.32|
|Election|0.11|0.18|
|Access to water|0.53|0.21|
|Public hospital|0.27|0.20|
|Private hospital|0.32|0.23|

Note: own calculations from the Uganda National Household Survey (UNHS) 1999/2000. 1. All district variables except distance to paved roads are constructed from dichotomous variables at the community level.

33
their potential for economic development and poverty reduction, the Heckscher-OhlinSamuelson effects need to be addressed properly by policy makers in both developing and developed countries.

# REFERENCES

Acosta, P., & Montes-Rojas, G. V. (2008). Trade Reform and Inequality: The Case of Mexico and Argentina in the 1990s. _The World Econom_ y, 31(6), 763-780.

Amsden, A. H. (1989). _South Korea and Late Industrialization_ . New York: Oxford University Press.

Anderson, J. B., & Dimon, D. (1999). Formal Sector Job Growth and Women’s Labor Sector Participation: the Case of Mexico. _The Quarterly Review of Economics and Finance_ , 39, 169191.

Athukorala, P. (2006). Trade Policy Reforms and the Structure of Protection in Vietnam. _The World Economy_ , 29(2), 161-87.

Athukorala, P. (2009). Transition to a Market Economy and Export Performance in Vietnam. _ASEAN Economic Bulletin_ , 26(1), 96-114.

Attanasio, O., Goldberg, P. K., & Pavcnik, N. (2004). Trade Reforms and Wage Inequality in Colombia. _Journal of Development Economics_ , 74, 331-366.

Baum, C. F., Schaffer, M. E., & Stillman, S. (2007). Enhanced Routines for Instrumental Variables/GMM Estimation and Testing. _The Stata Journal_ , 7(4), 465-506.

Belser, P. (2000). Vietnam: On the Road to Labor-Intensive Growth? _Policy Research Working Paper_ , 2389, the World Bank.

Benjamin, D., Brandt, L., Giles, J., & Wang, S. (2008). Income Inequality during China’s Economic Transition. In L. Brandt, & T. Rawski (Eds.), China’s Great Economic Transformation, Chapter 18. Cambridge: Cambridge University Press.

Bernard, A. B., Jensen, J. B., Redding, S. J., & Schott, P. K. (2007). Firms in International Trade. _Journal of Economic Perspective_ , 21(3), 105-130.

Bound, J., Jaeger, D. A., & Baker, R. M. (1995). Problems with Instrumental Variables Estimation When the Correlation between the Instruments and the Endogenous Explanatory Variable is Weak. _Journal of the American Statistical Association,_ 90(430), 443-450.

Brambilla, I., Porto, G., & Tarozzi, A. (2009). Adjusting to Trade-Policy Changes in Exports Markets: Evidence from U.S. Antidumping Duties on Vietnamese Catfish. _Policy Research Working Paper_ , 4990, the World Bank.

34
# **1 Introduction**

A poll featured in the _Financial Times_ of July 12, 2010 highlighted two striking facts. First, between 60 and 80 percent of the respondents in Western countries felt that budget cuts would help rather than hurt the economy; second, aid to developing countries was ranked first as a candidate for cuts in the U.S. and U.K., and second in all other countries. Against this background, in the words of a recent OECD document, “[t]here is a growing political demand among academics, NGOs, international agencies and voters for results in development.” (OECD 2010a).

The demand for evaluation applies to aid for trade (AFT) as well as to other forms of aid.<sup>1</sup> After declining as a share of Overseas Development Assistance (ODA) in the second half of the 1990s, AFT commitments have increased by 62% since the launch of the AFT initiative at the 2005 WTO Ministerial in Hong Kong, reaching $41.7 billion or 37% of “sector-allocable” ODA in 2008. For the EU, traderelated assistance (TRA) is an important part of the trade-and-development policy nexus, responding to a widely-perceived need to provide adjustment assistance to Southern partners affected by increasingly stringent product standards and by recent changes in the EU’s system of preferences (see te Velde et al. 2006).

What do we know about the impact of aid for trade (AFT)? The literature is limited. As for its allocation, Gamberoni and Newfarmer (2009) found that, after controlling for absorption capacity (governance etc.), it correlated with an indicator of ‘demand’ based on indices of under-trading. As for its impact, Wagner (2003) explored whether aid generated trade in the form of exports from the _donor_ country to the recipient (up to the early 1990s, over half of all bilateral aid was at least partially tied to donor exports); he found, using a gravity equation, that this particular form of trade was indeed boosted. By contrast, Osei, Morrissey and Lloyd (2004) ran a gravity equation in first differences on a panel of four European donors and 26 African recipients after testing for the direction of causalitybetween bilateral aid and trade flows. They found an unstable and, on the whole, insignificant impact of aid on trade (also in the form of exportsfrom donor to recipient). Nelson and Juhasz Silva (2008) used a moreconventional gravity equation including bilateral aid flows as a regressor (instrumented by their one-year lagged value) and found a significant although small elasticity, again, for flows from donor to recipient.

> 1Aid for Trade was defined by the 2006 WTO AFT Task Force through six categories: (i) Trade policy & regulations; (ii) Trade development; (iii) Trade-related infrastructure; (iv) Building productive capacity; (v) Trade-related adjustment; (vi) Other trade-related needs. The first three are referred to as Trade-related assistance (TRA); the last three are referred to as the ‘wider aid-for-trade agenda’ (EC 2008).

3
Table 15: Heterogeneous effects of savings default on total spending

||(1)|(2)|(3)|(4)|(5)|
|---|---|---|---|---|---|
|Panel A:|Male<br>HH head|Any previous<br>bank use|Close to<br>branch|Assets|Above median:<br>Patience|
|Savings Default|958.512|-2568.115|-651.466|-766.624|2203.133|
||(1391.385)|(1951.350)|(1510.431)|(1726.694)|(1953.386)|
|Observations|310|152|233|226|190|
|Mean of dependent variable in Cash group|16131.82|16846.46|16023.01|16754.24|15148.79|
|R-squared|0.296|0.442|0.337|0.301|0.288|
|Panel B:|Female<br>HH head|No previous<br>bank use|Far from<br>branch|Assets|Below median:<br>Patience|
|Savings Default|-1227.160|1645.099|543.324|672.508|-1104.029|
||(1753.121)|(1364.611)|(1684.321)|(1464.241)|(1289.129)|
|Observations|162|320|239|246|282|
|Mean of dependent variable in Cash group|13471.64|14328.71|14299.08|13531.83|15150.68|
|R-squared|0.207|0.203|0.204|0.208|0.275|
|P-value: equal efect of savings default|0.306|0.063|0.586|0.509|0.140|

The top panel includes respondents from female-headed households, those with above-median values for number of transactions at NBS in the 90 days preceding the transfer, those who live above the median distance from the bank branch, those with above-median values of a principle-index of asset ownership, and those with above-median patience, as measured at baseline by amount required to prefer a transfer in one month instead of immediately. P-values are from tests of equality of Savings Default coefficients in Panels A and B. All specifications include village and week-of-first-survey fixed effects, and the value of the outcome measured at survey 1. Exchange rate: MK 420 per USD. Robust standard errors in parentheses. * <u>p</u> _<_ 0.10, ** <u>p</u> _<_ 0.05, *** <u>p</u> _<_ 0.01 41
# **Remained Issues**

A successful reform requires the government to minimize the impact of oil price shocks on the economy. (1) In order to cut the public expenditures, the government has to streamline the staff in the civil service where 1.3 million people are employed. This is also a troublesome political issue. (2) Under the term of the IMF agreement, the Venezuelan government is obligated to set aside the surplus oil revenue, when the oil price received by the state oil producer, Petreleos de Venezuela (PDVSA), exceeds $14.7 per barrel. The surplus oil revenue will be put into two accounts: a debt rescue fund and a macroeconomics stabilization fund. The debt rescue fund is used for clearing overdue internal and external debt and for prepaying outstanding external liability. The stabilization fund first collects money while the oil price is high and then finances the government budget when the oil price drops to low levels. (3) Venezuela's public expenditure on education has been managed poorly, which is extremely biased toward high education, more than 50% for universities and only 47% used for the primary and secondary education. Only one third of the student population continue education beyond the 9th grade due to a high school dropout rate.

## Reference

1. World Bank. _Country Brief: Venezuela._ March 7, 1996.

2. Economic Intelligence Unit. _Country Profile: Venezuela._ London, United Kingdom. 1991/92, 1992/93, 1993/94, 1995/96, & 1996/97.

3. World Bank. _Venezuela Country Economic Memorandum: Living with Oil._ Volumes I & 2. June 21, 1995.

70
not necessarily causal. However, they motivate the possibility that informal redistributive arrangements could dampen labor supply levels.

**Figure 1:** Motivational Evidence: Redistribution and Hours Worked

<!-- Start of picture text --> Slope = -7.48<br>Slope = -4.17<br>0 .2 .4 .6 .8 0 .2 .4 .6 .8 1<br>Provided any money to family or friends Provided any money to family or friends<br>Country-region-ethnicity-level regression. N = 1010 Region-ethnicity-level regression. N = 338<br>Source: LSMS surveys; y-axis is total hours worked among adults aged 18-65 in a household Source: LSMS surveys; y-axis is total hours worked among adults aged 18-65 in a household<br>(A) West Africa (B) Côte d’Ivoire<br>Slope = -1.91 Slope = -8.58<br>.4 .6 .8 1 0 .02 .04 .06 .08<br>Provided any economic support to family or friends Received any money from family or friends<br>Municipality-ethnicity-level regressions. State-race-year-level regressions. N = 1074<br>Source: IFLS Wave 5, adults aged 25-55 Source: SIPP 2014-2020, adults aged 25-55<br>80 75<br>70<br>75<br>65<br>60<br>70<br>55<br>Average hours worked per week Average hours worked per week<br>65<br>50<br>42<br>42<br>41<br>40<br>38 40<br>Average hours worked per week Average hours worked per week<br>36 39<br><!-- End of picture text -->

# **(C)** Indonesia

# **(D)** United States

_Notes:_ Binscatter plots of the relationship between transfers in all years except the current year _t_ (x-axis) and hours worked per week in wage employment plus self-employment in year _t_ (y-axis). Panels A-B (C-D) display work hours for all adults in the household (for the individual respondent). Unit of observation is geographic sub-unit (determined by data availability) _×_ ethnicity/race _×_ year. The line of best linear fit and its slope are reported. Patterns are robust to dropping outliers.

In this paper, we develop a causal test to empirically examine this possibility. We conceptualize redistributive pressure as a “social tax” on earnings.<sup>3</sup> We focus on the domain levels and the general (time-invariant) tendency of a group to engage in transfers. In each panel, the negative correlations hold if we simply examine the contemporaneous correlations, and also if we remove outliers. 3We do not take a stance on the underlying microfoundation for redistributive pressure—such as second2
emissions from the power sector. Under the program, retailers and large electricity customers in NSW (and since 2005 in the Australian Capital Territory) are required to meet mandatory intensity targets to reduce (or offset) the emissions of GHG arising from the production of electricity they supply or use. They can meet their targets by purchasing certificates (NSW Greenhouse Abatement Certificates or NGACs). NGACs are generated through the following activities: low-emission generation of electricity and improved generator efficiency, activities that result in reduced consumption of electricity or on-site generation of electricity and carbon sequestration into biomass. Renewable Energy Certificates are also eligible<sup>62</sup> . No other form of credit (e.g. JI or CDM) is eligible at this time. A buy-out penalty applies, set at AU$11.50 (currently approximately US$9) for compliance year 2006. So far, all participants have been in compliance (eventually by carrying forward part of the shortfall – up to 10% of the benchmark). After the EU ETS, the NSW GGAS is the second largest greenhouse gas abatement market with about 20.2 million certificates exchanged through 2006 for a value estimated at US$225.4 million. The 2006 market represented a 3.3 times increase over the volumes transacted in 2005 and about 3.8 times increase in the value for 2005.

As of end of February 2007, 201 projects were accredited, for the most part under the “generation” and “demand side abatement” rules. Credits issued from carbon sequestration also entered the scheme in 2005. Over 40 million NGACs had been created by the end of March 2007, with “generation” certificates dominating at 70% of volumes followed by “demand side abatement” certificates at 25%. So far, taking into account the certificates that have been surrendered, there is currently an oversupply of over 13 million NGACs. Participants expect that the demand may exceed supply by 2009; however, the demand supply balance could quickly reverse as some participants may decide to hedge their position forward. In addition, there is growing interest in the voluntary market for the NGACs. The key to the supply/demand balance may in fact reside in the eligibility of NGACs under the future national scheme under discussion (see below). As long as no firm decision is made upon transition arrangements, some volatility is to be expected as has been the case in recent months.

Looking ahead, a national trading scheme is under discussion, to start no later than 2010 with the detailed design to be finalized by the end of 2008. Key inputs will be provided by the Garnaut Climate Change Review (with a final report due by end of September 2008). Meanwhile, an interim report released in February 2008, stated that Australia should promote strong global action on climate change and be prepared to match the commitments of other developed nations. Among

> 62 Their share in the total number of certificates surrendered for compliance tends to decrease from 29% in 2003 to 11% in 2006.

39
# **References:**

Adam, Christopher and Bevan, David (2003), Aid, Public Expenditure and Dutch Disease. CSAE Working Paper 184. Oxford: Centre for the Study of African Economies, Oxford University.

Adam, Christopher and Bevan, David (2006), Aid and the Supply Side: Public Investment, Export Performance, and Dutch Disease in Low-Income Countries. _World Bank Economic Review_ , 20, 261290.

Ahmad, E. and N. Stern (1987), Alternative Sources of Government Revenue: Illstrations from India, 1979-1980. In D. M. Newbery and N. Stern (eds.): _The Theory of Taxation for Developing Countries_ . New York: Oxford University Press.

Ahmed, S. and D. Croushore, (1994), The Marginal Cost of Funds With Nonseparable Public Spending. Working Paper 94-5, Federal Reserve Bank of Philadelphia.

Aitken, B. and Harrison, A. (1999), Do Domestic Firms Benefit From Foreign Investment? Evidence From Venezuela. _American Economic Review_ , 89.

Aiyar, Shekkar and Ummul Ruthbah (2008), Where Did All the Aid Go? A Macroeconomic Investigation of the Uses of Aid. Working Paper, no 08/34. Washington DC: International Monetary Fund.

Alfaro, Laura (2003), Foreign Direct Investment and Growth: Does the Sector Matter? Working paper, Harvard Business School.

Alfaro, Laura, Chanda, Areendam, Kalemli-Ozcan, Sebnem and Sayek, Selin (2006), How Does Foreign Direct Investment Promote Economic Growth? Exploring the Effects of Financial Markets on Linkages. NBER Working Paper no 12522. Cambridge, Ma: National Bureau of Economic Research.

Arellano, Manuel and Bond, Stephen (1991), Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations. _Review of Economic Studies_ , 58 , 277-297.

Auty, R. M. (2001), _Resource Abundance and Economic Development_ . Oxford: Oxford University Press.

Ballard, Charles L., John B. Shoven and John Whalley (1985), General Equilibrium Computations of the Marginal Welfare Costs of Taxes in the United States. _American Economic Review_ , 75, 128-138.

Barder, Owen (2006), A Policymaker’s Guide to Dutch Disease. Center for Global Development, Working Paper no 91.

Benge, M. (1999), Marginal Excess Burdens ofTaxes on Capital and on Labour Income in a Small Open Economy. Working Paper 364, Australian National University, Canberra, Australia.

Berg, Andrew, Shekhar Aiyar, Mumtaz Hussain, Shaun Roache, Tokhir Mirzoev, and Amber Mahone (2007), The Macroeconomics of Scaling Up Aid. Lessons from Recent Experience. Occasional Paper no 253. Washington DC: International Monetary Fund.

Berndt, Markus, Paolo Dudine, Jan Kees Martijn, and Abu Shonchoy (2008), The Spending and Absorption of Aid in PRGF Supported Programs. Working Paper no 98/237. Washington DC: International Monetary Fund.

29