rafmacalaba/datause-encoder-data huggingface dataset:
# 3. **Methodological issues**

Several important conceptual and methodological issues face researchers interested in studying democracy and inequality, which can broadly be classified into: measurement problems and selection bias.

# _A. Measurement problems._

# _(a) Income inequality_

The difficulties in accurately measuring _income inequality_ are well known. Data on income distribution are many times heterogeneous in regard to the timing of the observations, the definition of income and income recipient, the duration over which income is recorded, the proportion of the population covered, and the nature of the data collection procedure, which makes international comparisons exceedingly difficult. Some of the sources of this heterogeneity include whether the income figures are net (after cash transfers and taxes), gross (after transfers but inclusive of taxes) or factor only (before either taxes or transfers); whether income recipients are households or individuals; and whether the income figures are representative of the nation as a whole or refer only to certain regions or cities. Also, the dates the income.inequality figures refer to in existing data banks vary across nations. Consequently, a good portion of the observed country differences in inequality may simply reflect measurement artifacts. These data problems are yet further complicated by the fact that there are a number of data sources available, which somewhat differ in terms of coverage and some of the figures reported; they force research designs to be cross-sectional, which gives one very little leverage in addressing questions posed in dynamic terms. A major improvement took place only recently with the release of the Deininger-Squire panel 11
nonlinearities, we also regress WTP on household expenditure quartiles (column 3). Again, we see that that the wealthier a household, the higher is its WTP for electricity access, and the increase in the WTP is the highest for the wealthiest households.

Finally, we analyze the differential effect of expenditures on household WTP depending on the electricity consumption level by interacting WTP and the different consumption level scenarios (column 4). Consistent with the theoretical model, we see that the WTP increases significantly more with households’ income for grid electricity than for a solar lamp. A 1 percent increase in households’ expenditures increases their WTP for grid electricity by 0.23 percent. For a solar lamp, it increases only by half of that magnitude (0.12 percent). These effects are statistically significantly different. The increase in WTP for grid electricity with respect to households’ income is also higher compared to SHS by 0.02 percentage points, however, the difference is not statistically significant.

**Table 8: log of WTP in constant 2011 international $ (PPP)**

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
|Log of household expenditures|0.229***|0.183***||0.230***|
|in constant 2011 international $ (PPP)|(0.025)|(0.028)||(0.044)|
|Distribution of household expenditures:|||0.185***||
|2<sup>nd</sup>quartile (1 = Yes)|||(0.060)||
|Distribution of household expenditures:|||0.248***||
|3<sup>rd</sup>quartile (1 = Yes)|||(0.066)||
|Distribution of household expenditures:|||0.431***||
|4<sup>th</sup>quartile (1 = Yes)|||(0.073)||
|Interaction:||||‐0.024|
|SHS#Log of household expenditures||||(0.051)|
|Interaction:||||‐0.110**|
|Solar lamp#Log of household expenditures||||(0.049)|
|Country: Rwanda (1 = Yes)|0.454***|0.237**|0.104|0.236**|
||(0.091)|(0.106)|(0.105)|(0.105)|
|Country: Senegal (1 = Yes)|1.026***|1.091***|1.139***|1.098***|
||(0.087)|(0.083)|(0.084)|(0.084)|
|Log of the initial bid|0.201***|0.185***|0.185***|0.188***|

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# (1) Introduction

The experience in many developing countries over last few decades shows that economic liberalization delivered high income growth and impressive poverty reduction, but it also resulted in a signi...cant increase in inequality and corruption (see, for example, World Development Reports (1997, 2004, 2006)).<sup>2</sup> While a variety of factors such as returns to entrepreneurial risk taking and skill biased technological change contributed to the rise in inequality, there is also a growing recognition that a signi...cant part of the observed rise in inequality may be of the “wrong kind”, re‡ecting and reinforcing inequality of opportunities across generations, and driven, at least partly, by pervasive corruption. There is a widespread perception among general people that the fruits of economic growth have been skewed in favor of the rich, and the playing ...eld is not level.<sup>3</sup> The relevant policy question is how to reduce inequality without sti‡ing the dynamism of a liberalized economy that rewards e¤ort and entrepreneurial experimentation. There is a broad consensus in the academic literature and among the policy makers that education is among the most important policy instruments in this regard. For example, Stiglitz (2012, P. 275) notes “(O)pportunity is shaped, more than anything else, by access to education”, and Rajan (2010, P.184) argues “..the best way of reducing unnecessary income inequality is to reduce the inequality in access to better human capital”. A focus on building the human capital of the poor seems triply desirable: (i) it is the only asset that every poor person ‘owns’; (ii) human capital is inalienable and thus less susceptible to expropriation, an important advantage in many developing countries su¤ering from a lack of rule of law; and (iii) returns to education are expected to increase over time with globalization because of skill-biased technological change. Recognizing this unique role of education, a large number of developing countries over the last few decades invested heavily in policies such as free universal schooling (at least at the primary level), scholarships for girls, free books, and mid-day meals. The basic assumption is that such policies would lessen the burden on poor families for educating their children, and thus help reduce educational and income inequality

> 2 World Development Reports: Equity and Development (2006), Making Services Work for Poor People (2004), and The State in a Changing World (1997).

> 3 A recent survey by Pew Global attitudes project in China conducted in March and April of 2012 ...nds that about half of the respondents identi...ed increasing income inequality and corruption as “very big problem”, while 80 percent agree with the view that “rich just get richer while the poor get poorer.”

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# INTRODUCTION

Implementation issues appear to be critical in the success or failure of nutritior. interventions throughout the world. A 1989 meeting of the International Nutrition Planners Forum in Seoul, Korea (INPF, 1990) concluded that "how" a program is implemented may be as important, or in some cases more important, than the type of intervention. Yet we have little information on the process of implementing "successful' nutrition program or projects. This is particularly true for Africa.

The purpose of this paper is to focus attention on the implementation of nutrition interventions in Africa with the aim of identifying critical elements needed for effective implementation. This effort builds on earlier work conducted by Olayinka Abosede and Judith McGuire (Abosede and McGuire, 1989) in which the authors identified four factors that seemed to be present in successful nutrition programs; these elements were community participation, training, growth monitoring/growth promotion and supervision. These four elements were culled from four successful projects in Zimbabwe, Iringa, Tanzania, Senegal and Zaire.

The next step in identifying the components of successful implementation was to assess whether these same four elements were to be found in a iarger set of cases. In addition, we were interested in whether there were other crucial factors of implementation. The intent was to be as specific as possible for each element; for example, rather than simply saying supervision is important, going a step further with a more discrete analysis of number of workers per supervisor. number of encounters with workers per month, training needed for the supervisors etc.

This type of process analysis is rarely reported in evaluations of nutrition programs. Because of the dearth of information in the published literature, a mail survey was carried out
The cash balance is perhaps natural given most governments’ historical preoccupations with cash accounting and budgeting systems. It is also the most appropriate measure of balance if one is concerned with the fiscal stance of short-run stabilization policy, or with the public sector’s overall demands on capital markets, or with the aggregate level of tax revenues that are being postponed to future dates (Boadway, 1993).

In recent years, many governments have adopted accrual accounting principles in place of traditional cash accounting. Under accrual accounting, expenditures and revenues are charged to the year in which are incurred not when actually paid. Thus, any accounts receivable but not yet paid are treated as revenue received during the year and any accounts payable are treated as expenses even though the payment may take place in a different year. Unfunded pension liabilities owing in the future to civil servants under defined benefit programs are treated as a liability, and new pension liabilities would be an accrued expense to the current budget even though the payment would be many years hence.

Greater use of accrual information in government has led naturally to greater focus on operating balance as a measure of fiscal stance, in place of cash balance. The **operating balance** , which can be defined as (minus) the change in net worth of government, differs formally from the cash balance by the addition of net investment in capital, the change in the value of government financial assets less non-debt liabilities, including “implicit debt” associated with public pensions, government business enterprises, and the like.

When accrual accounting is adopted for the capital budget, capital expenditures are no longer expensed to the current year’s operations. Instead, they are depreciated over time reflecting an estimate of the capital good’s service life (the years by which the capital good provides benefits in the future). Thus, capital depreciation on current and past investment expenditures is charged as a current expense to the operating budget.

Naturally, a measure of fiscal balance that includes net investment in capital may be calculated whether the government has adopted accrual accounting principles or not; however, accrual accounting is most suited to the operating balance approach. Several governments, including Canada and Italy, have adopted accrual on a modified basis, in that accrual methods are not used for the capital budget. Table 1 provides a survey of public sector accounting practices in a number of countries.

When governments are constrained by fiscal rules, the operating balance may be preferred over the cash balance approach to limit “creative accounting” (Milesi-Feretti, 2003). Under cash accounting, governments may, for example, substitute unfunded liabilities (such as those related to contingent liabilities) for market debt as a means of satisfying constraints on borrowing. The operating balance approach, taking a broader perspective of fiscal sustainability, restricts the use of this and many other such 12
|8.1 WATERUSERS...................................................................................................................................................38|
|---|
|8.2 BRANTASBASINCORPORATION(PJT I).............................................................................................................39|
|8.3 THEPROVINCE...................................................................................................................................................40|
|8.4 DISTRICT-LEVEL GOVERNMENT.........................................................................................................................41|
|8.5 CENTRALGOVERNMENT....................................................................................................................................41|
|**9. CONCLUSION......................................................................................................................................................42**|
|**APPENDIX: VARIABLES IN THE ANALYTICAL FRAMEWORK................................................................44**|
|**TERMS AND ABBREVIATIONS...........................................................................................................................47**|
|**REFERENCES ..........................................................................................................................................................48**|

|Table 1: Land Use Data (hectare).................................................................................................. 9|
|---|
|Table 2: Production of Major Crops (1000 metric tons)................................................................ 9|
|Table 3: Population...................................................................................................................... 10|
|Table 4: Master Plans & Organizational Developments in the Brantas River Basin .................. 15|
|Figure 2: GDP Trend in East Java and Brantas Basin .................................................................. 10|
|Figure 3: Institutional Framework for Brantas Basin Management ............................................. 16|
|Box 2: Major Stakeholders of the Brantas River Basin................................................................ 20|

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Under the current assumption that ( _Lm_   _Ls ps_ ) > 0, _Z_  0 . If we further require that city earned    incomes ( [1 2 ( _t N N A_ )] ) be positive, _M_ must be positive. Given _Z_ is negative, _dy_ ( _N N A_ ) / _dR_ is negative.

In sum we have the following proposition relevant to our empirical work: **Proposition 1.** _If the city has a tradable manufacturing sector that is not too small relative to its local service sector so that_ ( _Lm_   _Ls ps_ ) _> 0, a decline in moisture will lead to an increase in urban population and total city income._ We could also look at changes in per capita incomes explicitly, although the direction should be obvious.<sup>11</sup> However, in our empirical work, total income or expenditure in the city will be measured by night lights data, which are recorded over time periods incompatible with the bulk of the population data. Income is nominal in a context where the price of services will change, but for a broad class of utility functions, the city’s sum of utilities is affected in qualitatively the same way as city income.<sup>12</sup> **3.3 Comparative statics with minimal local manufacturing** If the local traded good manufacturing sector is very small so ( _Lm_   _Ls_  _ps_ ) < 0, then the fortunes of the city are tied to the local agricultural sector, as in Jedwab (2011). We exposit this case assuming the local manufacturing sector exists, but the situation is analogous in the case where there is no manufacturing at all and the service sector technology (per worker output) is given by _bL_<sup></sup> _ss_ ,  _s_ 0 . In the new situation where ( _Lm_   _Ls_  _ps_ ) < 0, stability requires _Z_  0 . Now the sign of _dN A_ / _dR_ in eq. (10) is ambiguous. As a simple example, if  _y_  _ps_  0 , then _dN A_ / _dR_ < 0. In that case, as _Lm_  0, _dN A_ / _dR_  0 . When _Lm_  0 , the sign of _dN A_ / _dR_ depends entirely on the sign of  _y_  _ps_ . There, if  _y_  _ps_  0 , there is no effect of rainfall on the rural-urban population allocation, because migration effects only If _Z_  0 this expression is negative.

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than offset any advantage from greater productivity on the factory floor or from lower wage costs.

Many papers have analyzed the impact of a specific dimension of the investment climate, usually finding significant results. Bigsten et al. (2003) do find evidence of credit constraints among manufacturing firms in 6 countries in SSA. However, controlling for whether firms had a demand for credit and their productivity, the effects were significantly smaller. Nevertheless, size effects did remain, with larger firms more likely to receive a loan. Fisman and Raturi (2004) also find significant links between trade credit and the degree of competition. Competition can actually encourage trade credit as a means of gaining customer loyalty. However, competition can be limited by infrastructure bottlenecks and small market size.

Van Biesebroeck (2005) using manufacturing firm level data from nine African countries finds that credit constraints and failures in contract enforcement inhibit firms in the domestic market from exploiting economies of scale. However, Frazer (2005) finds that despite inefficiencies in the investment climate, at least in Ghana it is not the case that more productive firms are driven from the market and inefficient ones remain in business.

Collier and Gunning (1999a) argue that poor infrastructure is significant in promoting the proliferation and growth of small firms as local markets remain small. However, Clark et al. (2004) finds only weak evidence that transportation constraints lower exports. Bigsten et al. (2003) argue in favor of using more quantitative measures as subjective measures can be endogenous to firm performance. For example, SSA firms most likely to complain about infrastructure were those that were most productive, especially exporters. Using more objective information on the costs and time delays associated with infrastructure services is more convincing (Hallward-Driemeier and Aterido 2009).

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determinants of firm-level markups in formal manufacturing industries and then, using these markups as a proxy of product market competition, we examine the link between competition and firm-level outcomes such as productivity growth, employment and wages. This paper provides a novel contribution to the analysis of competitive conditions in South African markets in three ways: by generating additional evidence using a more comprehensive firm-level data set than most previous studies and by providing improved estimations of markups as well as new results on the link between competition and key economic outcomes. For example, we are not aware of any literature in the South African context that has linked behavioral proxies of competition, such as markup, to employment and wages.

# 1.1. Review of the literature

# _Measuring competition in South Africa_

In respect of markups, some evidence seems to suggest that manufacturing markups in South Africa have been significantly higher than they are in comparable industries world-wide (in particular in the United States) and they are also non-declining (Fedderke et al., 2007) manufacturing markups in the period 1990 to 1997; Aghion et al (2008) up to 2004). Fedderke et al. (2018) were the first to calculate firm-level markups for the South African manufacturing sectors using administrative tax data (SARS-NT panel). They find sector-specific relationships between markups, levels of market concentration and barriers to entry which might be one channel through which firms are able to maintain dominant positions in certain sectors. Additional empirical evidence by Klein (2011) and Fedderke (2013) also supports the conclusion that markups are relatively high. However, recent empirical work by Zalk (2014) and Du Plessis et al. (2015) points to conflicting findings suggesting that firms in South African manufacturing industries do not enjoy significantly higher markups than firms in comparator countries. While Zalk (2014) used similar data sets and price-cost margin (PCM) measures as Aghion et al (2008) but treated the data sets differently, Du Plessis et al. (2015) used different data sets. In addition, Edwards and Van de Winkel (2005) find average markups are below those in the United States and are close to the median of other countries. They ascribe the divergence from previous papers’ findings to the use of a different methodology as well as a different time horizon. More recently, De Loecker and Eeckhout (2018) have found a modest increase of markups in South Africa over the period from 1980 to 2016 using data primarily on publicly listed companies.

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# Footnotes

- **1/** In previous work (Faini et. al. 1989), we evaluated performance undet adjustment lending for a group of nine indicators using a before-andAfter approach so that we did not control for initial conditions nor for the size of external shocks.

- 2/ The World Bank initi-ated SALS (structural adjustment loans) and SECALs (sectoral adjustment loans) in 1979 and 1981 respectively. Like the EFF (Extended Fund Facility) and stand-by arrargements, World Bank adjustment loans are quick disbursing loans. For a description of adjustment lending investments by the **IMF** (World Bank) see IMF (1987), World Bank (1989). All IMF upper credit tranche programs are of short duration and some Funid-supported adjustment programs were initiated before 1979. However, of 288 programs during 1973-86, only 44 took place during 1973-78.

- 3/

- The following model draws on Goldstein and Montiel (1986).

- 4/ Because the choice of cut-off is arbitrary, we also carried out our estimation using 1981 as an alte:native cut-off point. The results were s.milar to those reported in table 3.

- 5/ The formula derives from a two-period maximization by firms and households under assumptions of perfect competition and wage-price flexibility. See Dornbusch (1985, pp. 354-6).

- 6/ One round of exclusion tests results in about 5 percent loss of observations. Excluded countries are reported in the appendix in Table A.2. The exclusion criteria were determined by the value of Cook's D-statistic. See Belsley, Kuh and Welsch (1980), and section A.3.

- 7/ Similar results, not reported here, were obtained in an alternative estimation based on a model in which CON is replaced by the intensity of IMF-WB adjustment lending.

- 8/ Because we fit the growth model to a relatively large number of countries, we kept it as simple as possible so that we were not able to distingu_sh between capacity and productivity effects nor between private and public investment.

- 9/ The 14 countries (see Table 4) were selected on the basis of the number of SALs. Turkey, included in that sample, had to be dropped from our analysis because regime changes did not allow us to get stable estimates.

- 10/ This interpretation is emphasized in a broader context in the literature on credibility (Calvo, 1986; Dornbusch 1988; Rodrik, 1988).
# **Figure 1 OECD index of regulatory restrictions in postal services**

<!-- Start of picture text --> Tunisia<br>Turkey<br>Italy<br>Hungary<br>United States<br>Switzerland<br>Mexico<br>Czech Republic<br>Canada<br>United Kingdom<br>Spain<br>Portugal<br>Poland<br>0 1 2 3 4 5 6<br>Restrictiveness index<br><!-- End of picture text --> Data source: Based on OECD (2005b).

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