rafmacalaba/datause-encoder-data huggingface dataset:
If the reforms would have gone ahead even in the absence of the aid we may still be interested to learn the economic impact of such reforms (since they are the types of policy which - donors support) but the impact of the reforms cannot be directly attributed to the aid. It is therefore importan **t** o address the two questions separately, as we do in Parts 4.2 and 4.3 respectively. Part 4.4 draws out the implications of this chapter's discussion for futrther research on aid effectiveness.

4.2 Does Aid Affect Policy?

The World Bank's reviews of adjustment lending (1988, 1990 and 1992) have reported indicators - of "compliance" that is the extent to which countries have actually implemented the reforms outlined in the various agreements relating to adjustment loans.

Mosley _et al._ (1991 Volume 1: 134-145) argue that these compliance measures do not give an accurate picture of the extent of reform since some measures are very easy to implement whereas others may prove impossible to do so because of either poor design or changes in the external environment. If our concern is to trace causation from aid to policy to performance we must take their argument very seriously: compliance simply is not a measure of the degree of reform, and so is not a suitable variable to use in such analysis. There are two problems here. Since complilance measures cannot tell us the extent of actual changes which have occurred they cannot tell us how much reform aid has really supported. Second, these indicators are therefore not the appropriate variable for analyzing the macroeconomic impact of reform. This litter point is returned to in Part 4.3.

- Furthermore, compliance indices are a form of before versus after approach all changes. in policy since the star-t of adjustment borrowing are attributed **to** that borrowing. No attempt is made to determine the piolicies that would have occurred in the absence of the adjustment loan. As argued in Chapter 2, before versus after is not a satisfactory method for determining causality.

But a more serious underlying problem is that the presence of a program is fl the - relevant exogenous variable, it is the p.olicies which are themselves pursued this point was partly recognized in the World Bank's (1992) third report on adjustment lending, which suggested that the analysis of the impact of adjustment borrowing should consider the change policies rather than the presence or not of adjustment borrowing. This suggestion has been followed up in an intrnal review of the adjustment experience in sub-Saharan Africa [tis publication is not yet in the public 71
Because investment decisions are made by households, the firm’s problem is static; firms demand _k_ and _l_ , whereas _g_ and _z_ are taken as exogenous variables. Each firm pays the competitively-determined wage, _w_ , on the labor it hires and the rate _r_ on the capital it rents. Furthermore, since _f(·)_ shows constant returns to scale in private factors - _k_ and _l -_ , profits are zero and optimally leads to the usual marginal productivity conditions: Following Romer (1986), the average capital stock across firms is taken as a proxy for the knowledge index available to each single firm. While firms decide on _k_ , the other two variables _g_ and _z_ are outside of their control. Since firms are assumed to be identical, the average capital in the economy is equal to _k_ at equilibrium (i.e., _z=k_ ), and overall per capita production is given by: Since each firm neglects its own contribution on the aggregate capital stock, notice that ∂ _F_ (·) / ∂ _k_ and ∂ _f_ (·) / ∂ _k_ are not equal: ∂ _f_ (·) / ∂= _k_ α _y_ / _k_ while ∂ _F_ (·) / ∂= _k_ (α +φ) _y_ / _k_ , i.e., the social return to accumulated capital is higher than the private return.

# **Households**

There exist a large number of identical infinitely lived households that allocate resources between consumption, _c_ , and investment in physical capital, _i_ . Every period consumption is valued according to a Constant Elasticity of Substitutions (CES) utility function:<sup>13</sup> where β is the discount factor, between zero and one, and 1/σ is the constant elasticity of intertemporal substitution (EIS), also between 0 and 1. Private capital accumulates over time according to the following expression: where δ is a linear depreciation rate of private capital, between zero and one. Because δ <1, this specification allows for long-lived private capital, which is a relevant and realistic element in the model.

> 13 The Cobb-Doulas for technology and the CES for utility are functional forms required for the existence of a balance growth path in this economy.

6
**Table 3: Household Level Descriptive Statistics by Treatment Status**

||To|tal|Con|trol|Treat|ment||
|---|---|---|---|---|---|---|---|
||Mean|SD|Mean|SD|Mean|SD||
|Head's age|45.317|15.392|45.533|15.578|44.980|15.099||
|Married couple|0.711|0.454|0.707|0.455|0.717|0.451||
|With legal marriage certificate|0.764|0.425|0.752|0.432|0.782|0.414||
|Female headed household|0.224|0.417|0.239|0.426|0.201|0.401|**|
|Head has at least primary education|0.326|0.469|0.320|0.467|0.335|0.472||
|Head reads and writes|0.617|0.486|0.611|0.488|0.628|0.484||
|Number of male children age 14 and less|0.900|1.044|0.899|1.045|0.902|1.044||
|No. of female children age 14 and less|0.899|1.031|0.909|1.044|0.884|1.011||
|Number of adult male age 15 to 60|1.190|0.899|1.189|0.900|1.193|0.898||
|Number of adult female age 15 to 60|1.303|0.917|1.280|0.880|1.339|0.971||
|Male members age 60 and above|0.116|0.321|0.116|0.320|0.117|0.322||
|Female members age 60 and above|0.122|0.330|0.130|0.341|0.108|0.311||
|Land holdings in hectares|0.932|1.742|0.909|1.805|0.968|1.639||
|Total number of households|22|68|13|69|88|6||

**Source:** Own computation from 2010 World Bank Land Tenure Regularization Survey

**Note:** Significance levels are reported for t-tests of the equality of the means for each of the variables between control and treatment areas (* significant at 10%; ** significant at 5%; *** significant at 1%).

19
_Tax Reform in Transition_ 21

# **_4. Conclusions_**

The analysis of the 1992 household budget survey indicates that Bulgaria can benefit from a much simpler and lower income tax structure than the one which prevailed in 1992. Two possible types of alternative income tax systems have been explored, a flat rate and a progressive, but simpler three-bracket rate system, and their implications for potential revenue and income distribution. The analysis suggests that each of these alternative systems would have been more efficient in terms of potential revenues, while increasing the protection to the poor through increasing the exemption level, i.e., revenue-enhancing and redistributive tax reform. The results are robust to the inclusion of the existing significant tax evasion.

The actual developments since 1992 have, first, moved Bulgaria even further away from the proposed simple income tax systems. In particular, the 1993 amendments to the 1992 personal income tax have complicated the system in two major ways. First, while the 1992 marginal income tax rates were not low by international standards, the rates implemented in the 1993 amendment were even higher, with top rate rising from 40 to 52 percent. Second, the number of tax brackets were increased from 7 to 10, with three additional brackets having higher rates of 44, 48, and 52 percent. These more complex and higher rates are almost certain to complicate administration and enforcement, and provide powerful additional incentives for tax evasion. Fortunately, the country began to move toward less nominal progressivity in its personal income tax structure, following the 1997 tax reform program.

But whichever alternative income tax structure is chosen, it should be clear from the above analysis that the 1992 system and, even more so, the 1993 amended income tax system has inferior characteristics to simpler and more efficient alternatives. Therefore, further efforts in improving the income tax system in Bulgaria must aim to raise the exemption level, set the rates as low as possible, and reduce the number of brackets and define them as broadly, yet realistically, as possible. Reform in this direction would not only improve the revenue performance of this important tax, but also improve its protection of the poor. The government has made significant progress in adopting several of these measures in its 1997 tax
- 1) **Market income** includes gross income from labor (wages and income from selfemployment, both from informal<sup>7</sup> and formal employment), capital income, income from private transfers, self-production consumption as well as imputed rent

- a. **Labor income** includes: income from dependent employment, different types of self-employment (entrepreneurship, agriculture, professional practices, household help, selling or reselling products, private services and other business activities)

- b. **Capital income** includes: income from rent, dividends and interest

- c. **Income from private transfers** includes: net (amount received minus amount paid) financial assistance and alimony paid by the household, remittances and private pensions

- d. **Imputed rent** includes estimated value of monthly rent that the house-owners would pay if they had to rent their living space

- e. **Self-produced consumption** is the market value of goods produced for own consumption deducted from expenses incurred in the process of production of goods for own consumption

- f. **Other income** includes reported income for which no source was reported and labor income for children under 16 years of age

- 2) **Market income plus pensions** is calculated based on the Market income (1) from which the total amount of pension contributions is deducted, while pensions (old-age, disability, survivors, agriculture and abroad) are added

- 3) **Net market income** is based on Market income plus pensions (2) from which we deduct direct taxes, health and unemployment insurance contributions

- 4) **Disposable income** is calculated as the sum of the Net market income (3) and direct transfers

- 5) **Consumable income** is calculated as the difference between Disposable income (4) and indirect taxes and indirect subsidies (heating and utility allowance)

- 6) **Final income** is calculated as the sum of Consumable income (5) and in-kind health and education benefits

Comparing the income distribution across these different income concepts helps to evaluate the impacts of the fiscal system and of specific fiscal intervention on inequality and poverty. Market income in this analysis includes imputed rent value for owner-occupied housing to enable cross-country comparison, following the Commitment to Equity method in the Guidebook. The poverty and inequality estimates differ slightly from official estimates based on the SILC, which do not include imputed rent in the income aggregate. Appendix 2 includes a robustness analysis for when imputed rent is excluded, where the direction of the results remains valid even though the levels can differ.

The treatment of pensions and pension contributions is often not straightforward. There is no clear consensus: on the one hand, contributory pensions can be treated as personal savings or deferred income; on the other hand, pensions can be treated as government transfers. Pensions

> 7 Informally employed in this context are workers who do not have a written contract with their employer or workers not paying pension and health insurance contributions.

11
**Figure 1: Sector of nonfarm enterprises (%)**

Period 1, 2018/2019 <!-- Start of picture text --> Trade 44.145.6<br>Manufacture or sale of local beverages 1.3 23.4<br>Manufacturing clothes 0.3 9.1<br>Manufacturing food 2.0 6.3<br>Other manufacturing 2.5 8.4<br>Food and beverage services and hotels 4.8 14.0<br>Transportation services 0.1 6.5<br>Other personal services 6.6 13.9<br>Construction 0.11.2<br>Others 2.5 7.2<br>0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0<br>Male-owned Female-owned<br><!-- End of picture text --> Period 2, 2021/2022 <!-- Start of picture text --> Trade 44.0<br>43.0<br>Manufacture or sale of local beverages 2.7 28.6<br>Manufacturing clothes 1.5 5.4<br>Manufacturing food 2.2 6.7<br>Other manufacturing 3.4 7.8<br>Food and beverage services and hotels 5.35.4<br>Transportation services 0.1 12.1<br>Other personal services 1.02.7<br>Construction 0.2 8.6<br>Others 5.6 13.6<br>0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0<br>Male-owned Female-owned<br><!-- End of picture text --> Source: Author’s calculations using ESS 2018/2019 (period 1) and ESS2021/2022 (period 2).

Most are microenterprises (defined as having five employees or fewer) and 94% of female businesses are sole proprietors (with no employees) compared to 83% of male businesses (Table 3).<sup>12</sup> Female enterprises earn less revenue and are less likely than male enterprises to be registered. Manufacturing or sale of local beverages – a female-dominated activity – generates the lowest median annual sales of all the sectors (Table 12 The government defines microenterprises to be those with no more than five employees and assets valued at or less than 1 million birr (World Bank 2021).

10
# _4.2. Precipitation trends_

Using the same methodology as above, the precipitation data for 24 stations are analyzed to detect systematic trends. All the 24 precipitation anomaly series are plotted in Appendix B. Table 6 shows that 4 stations had a significant negative trend in precipitation, 3 stations had a significant positive trend, but the majority of stations (17) had no significant trend at all.

**<u>Table 6: Estimated precipitation trend (mm/decade) for 24 stations in Peru</u>**

|**Station**|**Trend**|**t-value**|**P-value**|**# of obs.**|
|---|---|---|---|---|
|AREQUIPA|-0.8564|-1.27|0.206|608|
|AUGUSTO WEBERBAUER|1.8484|1.62|0.107|511|
|CAJAMARCA|0.0183|0.01|0.992|379|
|CAMPO DE MARTE|-0.2280|-4.02|0.000|374|
|CHACHAPOYAS|0.0819|0.04|0.972|398|
|CHICLAYO|-1.0942|-1.49|0.136|609|
|CUZCO|-0.8844|-0.76|0.446|578|
|GRANJA KCAYRA|0.7333|0.66|0.512|438|
|IQUITOS|12.8737|5.06|0.000|679|
|JUANJUI|0.3905|0.13|0.897|390|
|JULIACA|-2.4703|-1.44|0.151|392|
|LA PAMPILLA|-0.4479|-0.78|0.437|423|
|LIMA-CALLAO/AEROP.|-1.3658|-1.55|0.122|502|
|PISCO|-1.2435|-3.13|0.002|624|
|PIURA|2.2242|1.25|0.212|537|
|PUCALLPA|-3.0125|-1.34|0.180|575|
|SAN JUAN|-0.6679|-1.20|0.233|430|
|TACNA|-1.0533|-5.64|0.000|556|
|TALARA|3.7294|2.66|0.008|513|
|TARAPOTO|-3.1772|-2.46|0.014|611|
|TINGO MARIA|-0.6414|-0.13|0.893|424|
|TRUJILLO|0.1481|0.37|0.709|541|
|TUMBES|7.3707|2.46|0.014|387|
|YURIMAGUAS|-0.1102|-0.04|0.966|446|

_Source:_ Authors’ estimation based on data from the NCDC’s Monthly Climatic Data for the world.

There seem to be no systematic differences between regions. Among the coastal stations, three showed a reduction, two showed an increase and five no change. Among the mountain stations, all stations showed no significant change. Among the rainforest stations, one showed increase, one showed decrease and four showed no change.

In no region is there convincing evidence of a systematic change in precipitation, so for the purpose of simulation in the following section, we will assume no change in precipitation patterns over the last 50 years.

13
# **How Should Donors Respond to Resource Windfalls in Poor Countries? From Aid to Insurance**

Anton Dobronogov<sup>‡</sup> , Alan Gelb<sup>↨</sup> and Fernando Brant Saldanha<sup>◊</sup> _Keywords:_ countercyclical, foreign aid, hedging markets, low-income countries, macroeconomic stabilization, natural resources, volatility.

_JEL classification codes_ : E63, F35, G23, Q33 ‡ World Bank, adobronogov@worldbank.org ↨ Center for Global Development, agelb@cgdev.org ◊ SDA Gestao de Recursos, Rio de Janeiro, Brazil, fsaldanha@alum.mit.edu We are grateful to Kevin Carey, Sebastien Dessus, Farrukh Iqbal, Ben Leo, John Litwack, Jacques Morriset, and Jean-Pascal Nganou for constructive comments and to David Santley for updated information on the oil sector in Uganda.
Table 2: Predictions 1 and 2: Effects on Types of Candidates and Winners

|**Panel A**|**Female**<br>**winner**|**# Female**<br>**candidates**|**# Male**<br>**candidates**|**# Independent**<br>**candidates**|**# Party-afliated**<br>**candidates**|
|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|
|_Treat_|0.222|0.046|-5.099|-3.988|-1.002|
||(0.091)**|(0.208)|(2.230)**|(1.909)**|(0.780)|
||[0.059]*|[0.332]|[0.059]*|[0.059]*|[0.111]|
|**Panel B**|||**First**|**Stage**||
|_Cut-of_|-0.202**|-0.217**|-0.201**|-0.201**|-0.195**|
||(0.084)|(0.081)|(0.085)|(0.085)|(0.086)|
|Untreated _y_ Mean|0.052|0.466|9.680|5.263|4.897|
|Observations|1,564|1,816|1,596|1,586|1,532|
|State FE|x|x|x|x|x|
|Year FE|x|x|x|x|x|
|State*Year FE|x|x|x|x|x|
|Clusters|211|242|215|214|207|
|Bandwidth|12.339|14.231|12.472|12.424|12.102|

_Notes: y_ refers to the dependent variable. Estimates are for unreserved seats only. Robust standard errors clustered by the running variable in parentheses. Anderson (2008) q-values in square brackets. Bandwidth is reported in female literacy rate percentage points around treatment cut-off of 39.3 percent. *** _p <_ 0 _._ 01 ; ** * _p <_ 0 _._ 05 ; _p <_ 0 _._ 10.

women from entering politics in India, especially at the state level), the DPEP increased the number of female contestants by 10 percent. Additionally, the number of male contestants per constituency experienced a statistically significant 50 percent decline. The results in columns (2)-(3) translate into an increase in the fraction of candidates that are female in treated districts relative to untreated districts.

Column (4) further reveals that the male dropouts in treated districts are overwhelmingly independent candidates, whose numbers decline by 3.99 (76 percent) on average. These independent candidates are the most marginal ones in state elections, with a win rate of only 1.72 percent in over 9,000 elections in unreserved seats in our sample. The number of candidates from official political parties, on the other hand, remains largely unchanged postprogram in column (5). These results are consistent with the model’s insight of marginal, low-competence male candidates being the ones dropping out from contesting elections as a result of the implementation of the DPEP.

# **6.2 Prediction 3: Effects on Candidate Competence**

Our model predicts that the DPEP should lead to an increase in the competence threshold for male candidates to run for office and reduce the threshold for female candidates. Thus, the 19
# **Socioeconomic Impacts of COVID-19 in Four African Countries**

Anna Josephson<sup>†</sup> , Talip Kilic<sup>‡</sup> , Jeffrey D. Michler<sup>#1</sup>

**JEL Codes:** C83, I15, I31, O12.

**Keywords:** SARS-CoV-2, COVID-19, behavioral change, income loss, household enterprises, access to basic needs, food insecurity, concerns, access to basic needs, access to education, Ethiopia, Malawi, Nigeria, Uganda, Sub-Saharan Africa.

> 1 † Department of Agricultural and Resource Economics, University of Arizona, <u>aljosephson@arizona.edu. ‡</u> Development Data Group, World Bank, Washington, DC, tkilic@worldbank.org.<sup>‡</sup> Department of Agricultural and Resource Economics, University of Arizona, jdmichler@arizona.edu.
<!-- Start of picture text --> ... . : : ENVIRONMENT ( EPIDEMIOLOGIC, ECONOMIC, POLITICAL)<br>. . . . . .. .. . .. . . .. . . . . . . . . . . . . . . .<br>..:... :':~ ~ ~ ~ ~ ~ ~~~~~ ACTOR.S ~ ~~~~~~~........ .. . I..TERVEI..G . .:: : OR A VARIABLES I A I N D S G ::'--- OCTIVES ..... ............ PRODUCTS .... ........<br>Managerial Decision Making POLICIES-<br>J~MANAGERtIAL<br>MANAGFIERS Managerial Skills EfICIENCY SUPPORT<br>Managerial Autonomy SERVICESS<br>HEALTH<br>. Design of Production SERVICE CARE-:<br>:' Process EFEICIENCY SERVICES<br>Clinical Decision Making<br>CLiiTICAL<br>1ciA p< Clinical Skills EFFICIENCY HEALTH<br>_________________Clinical Autonomy<br>.~~ ~ ~ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~.. ... . .. ..<br><!-- End of picture text -->

# Figure I

# CONCEPTUAL FRAMEWORK FOR THE STUDY OF HOSPITAL 6FFIC[ENCY
**Figure 13: Effect of real GDP per capita growth on the female labor force participation rate**

<!-- Start of picture text --> 0.8<br>0.6<br>0.4<br>0.2<br>0.0<br>-0.2<br>1960 1970 1980 1990 2000 2010 2020<br>Range of variation GDPpc<br>Percentage points<br><!-- End of picture text --> Source: Own calculations.

In contrast, the second period, from 1980 to 1995, displays a negative trend. This period includes the economic crises of the early 1980s. According to Magnac (1992), during this crisis, young women withdrew from the labor force but re-entered the market as soon as the crisis was over. It is worth mentioning that according to Tenjo, Álvarez, and Jiménez (2016), the gap between unemployment rates among men and women widens during economic recessions.

The third period, between 1996 and 2002, exhibits a change in the trend, compared to the previous period, from negative to positive in the effect of the real GDP per capita growth on the female labor participation, starting in 1996 (Figure 13). This period was characterized by an increase in unemployment and by a dramatic deterioration in economic activity, which worsened in 1998 and 1999 due to the international crisis that deteriorated the country’s terms of trade and reversed capital flows, in a context of economic instability.<sup>13</sup> This economic crisis reduced family income, which led to an increase in the labor supply of some household members to compensate for this loss of income; in particular, the wives who, until then, did not participate in the labor market. This effect is known as the “added worker” effect.<sup>14</sup> The fourth period, from 2003 to 2018, was characterized by continuous economic growth, except for 2008-2009 and 2016-2017 when there was a slowdown in economic activity. The growth during this period was mainly driven by the boom in raw material prices. The impact on the _f_lfp_r_ was positive and increasing, with an average coefficient of 0.29pp. During the first years of this period, 2003-

> 13 For more details about the crisis of 1999, see Pérez-Reyna (2017).

> 14 See, for example, López Castaño (2001) and Santamaría and Rojas (2001) for an analysis of the added worker effect during the 1999 economic crisis in Colombia.

23