rafmacalaba/datause-encoder-data huggingface dataset:
these countries’ needs at low costs.<sup>7</sup> By contrast, this paper studies _all_ aspects of the financial system in the second largest developing country and finds that many results based on existing crosscountry studies to a large degree do not apply to India. Our paper thus complements cross-country studies, and can further advance the understanding of growth mechanisms.

We also utilize surveys to examine small- and medium-scale private firms, which is one of the most vibrant corporate sectors in India. Survey-based research has made significant contributions to the law, institutions, finance and growth literature.<sup>8</sup> In particular, the World Bank has carried out a series of country- and firm-level surveys on the business environment in more than 80 countries, including both India and China (e.g., Cull and Xu 2005). Our survey differs from the World Bank surveys in two ways. First, the main goal of the World Bank surveys is to examine the degree of “convergence” of institutional development in emerging countries toward institutions in developed countries (in particular, the U.S.), while our goal is to uncover and analyze factors that can be effective for extended periods in supporting firm- and economy-wide growth. Second, our surveys provide the most comprehensive and detailed information on all the financing channels (standard and alternative) and governance mechanisms (formal and informal) at different stages of non-state, non-listed firms, which have been generally overlooked in the literature.

The rest of the paper is organized as follows. Section II provides background information on India, and Section III describes the size and growth of the different sectors of the Indian economy. In Section IV, we examine the financing patterns, valuation, and dividend policies of firms in the Listed Sector. Section V presents our survey results of small- and medium-scale firms. Finally, Section VI concludes. Appendix A contains the explanations of all the variables used in the paper.

> 7 Moreover, Stulz (2005) argues that there are limits to globalization, including the improvement of institutions, due to a “twin” agency problem of governments and corporate insiders in emerging countries.

> 8 For example, DLLS (2003) conduct worldwide surveys on the efficiency of judicial systems, while Johnson, McMillan, and Woodruff (2002) conduct firm-level surveys in economies of transition on property rights and finance.

6
# **References**

- Alesina, A. F. & Dollar, D. (2000), Who Gives Foreign Aid to Whom and Why?, _Journal of Economic Growth_ **5** (1), 33-63.

- Amegashie, A. J., Ouattara, B. & Strobl, E. (2007), Moral Hazard and the Composition of Transfers: Theory with an Application on Foreign Aid, CESifoWorking Paper No. 1996, CESifo.

- Bailey, R. (2009), The Right to Survive in a Changing Climate, Oxfam Background Paper, Oxfam International.

- Bermeo, S. B. (2007), Utility Maximization and Strategic Development - A Model of Foreign Aid Allocation, mimeo, Department of  Politics, Princeton University.

- Berthelemy, Jean-Claude & Tichit, A. (2004), Bilateral Donors’ Aid Allocation Decision - a three-dimensional Panel Analysis, _International Review of Economics & Finance_ **13** (3), 253-274.

- Besley, T. & Coate, S. (1991), Public Provision of Private Goods and the Redistribution of Income, _American Economic Review_ **81** (4), 979-984.

- Burnside, C. & Dollar, D. (2000),  Aid, Policies, and Growth, _American Economic Review_ , **90** (4), 847-868.

- Correlates of War 2 Project (2008), Colonial/Dependency Contiguity Data, 1816-2002., _http://correlatesofwar.org_ Version 3.0.

- Currie, J. & Gahvari, F. (2008), Transfers in Cash and In-Kind: Theory Meets the Data’, _Journal of Economic Literature_ **46** (2), 333–383.

- Doocy, S., Gabriel, M., Collins, S., Robinson, C. & Stevenson, P. (2006), Implementing Cash for Work Programmes in Post-Tsunami Aceh: Experiences and Lessons Learned, _Disasters_ **30** (3), 277–296.

- Dubin, J. A. & Rivers, D. (1989), Selection Bias in Linear Regression, Logit and Probit Models, _Journal of Economic Growth_ **5** (1), 33–63.

- Dudley, L. & Montmarquette, C. (1976), A Model of the Supply of Bilateral Foreign Aid’, _American Economic Review_ **66** (1), 132–142.

- Eisensee, T. & Strömberg, D. (2007), New Floods, New Droughts, and U.S. Disaster Relief, _Quarterly Journal of Economics_ **122** (2), 693–728.

- Fink, G. & Redaelli, S. (2009), Determinants of International Emergency Aid: Humanitarian Need Only?, World Bank Policy Research Working Paper No. 4839, The World Bank.

13
system. Those same individuals could be measured as poor at market income, when pensions are not included.

These individuals would be, in a sense, “false poor” as their most likely outcome (in retirement) without a public contributory pension system would be an income level (in retirement) that depends on the accumulated earnings on assets held in privately arranged retirement accounts. The creation of this “false poor” population would also automatically cause an overestimate of the redistributive impact of fiscal policy.<sup>15</sup> Therefore, the _baseline results_ (discussed below) are based on the PDI treatment of the Ugandan public contributory pension system. Nonetheless, throughout the report, we also present the results produced under the PGT treatment and overall, the results are very similar. Market Income plus Pensions is thus our baseline “pre-fiscal” income (income prior to any government intervention), and pensions are not included in the list of fiscal instruments.

# 3.4. Allocating Assumptions

## 3.4.1. Direct Taxes

Households who are PAYE-liable are identified directly in the UNHS consumption expenditures module as households that reported paying income tax. PAYE amounts paid (as reported in the consumption module) were used to generate shares of total PAYE revenues contributed by UNHS households. The amount of PAYE allocated in the survey was generated by first scaling total PAYE collections in administrative and budget reporting such that the ratio of total PAYE revenues in administrative records to National Accounts (NA) Household Final Consumption Expenditure was equivalent to the ratio of PAYE collected from UNHS households to total UNHS Consumption Expenditures. The PAYE burden for each household was then determined by applying each household’s share to the scaled PAYE amount.

## 3.4.2. Direct Transfers

The SCG and NUSAF programs provide direct cash transfers to eligible individuals; whereas UWEP and YLP provide soft loans to qualifying _groups._ The UNHS does not allow direct identification of beneficiaries for any of these programs. Instead, we use the program reports discussed in section 2.2.2 (from the Ugandan executing agencies as well as multilateral development agencies) to understand eligibility, coverage, and benefit levels per region and to parameterize eligibility and generate transfer-eligible populations within the UNHS.

For SCG, we identify eligible households as those that include an individual over 65 years of age not receiving an official government pension. We calculate a per capita subsidy amount from the government

> 15 For a more detailed discussion, see the CEQ Handbook, Lustig (2018, p21).

17
**App. Table 1a:  Largest US companies hiring workers in India**

|N|Number of contracts<br>with worker in India|India's share of total<br>contracts originating<br>from company|Company contact has<br>ethnic Indian name|US State|
|---|---|---|---|---|
|(1)|(2)|(3)|(4)|(5)|
|1|118|1.00|No|Virginia|
|2|94|0.98|No|California|
|3|73|0.26|No|Florida|
|4|62|0.93|No|Virginia|
|5|53|1.00|No|Connecticut|
|6|51|0.98|No|Wisconsin|
|7|46|0.38|No|Florida|
|8|45|0.68|Yes|New York|
|9|44|0.39|No|California|
|10|42|0.36|No|Nevada|
|11|40|0.56|No|Arizona|
|12|40|0.63|No|California|

# **App. Table 1b:  Largest non-US companies hiring workers in India**

|N|Number of contracts<br>with worker in India|India's share of total<br>contracts originating<br>from company|Company contact has<br>ethnic Indian name|Primary country|
|---|---|---|---|---|
|(1)|(2)|(3)|(4)|(5)|
|1|906|0.58|Yes|United Arab Emirates|
|2|68|0.36|No|United Kingdom|
|3|58|0.53|No|United Kingdom|
|4|46|0.84|No|Italy|
|5|45|0.34|No|Australia|
|6|44|1.00|No|Netherlands|
|7|42|0.14|No|Spain|
|8|40|0.38|No|Australia|
|9|39|0.87|No|United Kingdom|
|10|29|0.31|No|Australia|
|11|29|0.32|No|United Kingdom|
|12|29|0.63|No|Denmark|
# 4.3 Extension to Public and Benchmark Strategies

In this section we extend the regression analysis to the binary variables distinguishing between public debt management strategies made available to the public and those not available to the public, and further between strategies formulated in terms of benchmarks and those in terms of guidelines. We thus try to explain two additional binary variables yi<sup>Pandy</sup> i<sup>Bde...nedas</sup> Again we opt for the PROBIT model<sup>21</sup> when investigating to what extend can yi<sup>Pandy</sup> i<sup>B</sup> be explained by selected economic indicators Xi. Since the number of observations in our sample available for estimation changes noticeably due to a differing number of observations available for each explanatory variable we resort to the speci...c-to-general approach to build up the ...nal models estimated for yi<sup>Pand</sup> yi<sup>B.WestartwithGDPpercapitaandaddonotherrelevantvariablesaccordingto</sup> their signi...cance while maximizing the coverage of the survey data. We ...rst discuss some additional variables that appear in the PROBIT model for yi<sup>Pandy</sup> i<sup>B,and</sup> which were not signi...cant when used to explain existence of a strategy, i.e. yi.

GDP growth - when economy performs well and is experiencing higher growth rates of GDP the government may be more willing to become transparent about its actions and decisions. This argument implies that with higher GDP growth government’s capacity in meeting public’s demand for higher transparency in public debt management grows as well. The series of GDP growth was obtained from the Penn World Tables (Heston et al, 2006).

Terms of trade volatility - this variable captures the intensity of real external shocks that hit the economy. Higher risk of real external shocks, as measured by the standard deviation, creates a genuine dilemma for country authorities of whether to

> 21We have carried out the estimation using LOGIT and LP models as well to check on any mispeci...cation problems. We did not detect any. The estimation results are available from the author.

23
# **3.1 Study Sample and letter template**

Our sampling frame is the Employment Services of South Africa (ESSA) database, consisting of more than 550,000 job seekers collected by the Department of Labour (DoL). We restricted this sampling frame to African unemployed youths between the ages of 18 and 34. We limit our study sample to job seekers who have some form of previous work experience (as our intervention tests reference letters from previous employers), have not completed university-level tertiary education and live within traveling distance from our implementing labor centers.

We further stratify the sample by gender to facilitate subgroup analysis. In the recruitment call, surveyors explain that the job seeker is invited to participate in an employment service study at the local labor center on a specified day. In return, they receive a stipend of 30 Rand (~ 2 USD) to cover travel costs. Across all experiments, 67% of the successfully contacted unemployed individuals agreed to participate.<sup>6</sup> A baseline survey is administered through an in-person interview at the labor center. In Experiment 1, this is followed by an aptitude test that evaluates basic math and literacy skills.<sup>7</sup> The study employs an encouragement design implemented in cooperation with the DoL. After the baseline survey, participants assigned to the treatment group have a brief individual meeting explaining how to use reference letters in the job search. This is followed by a discussion of the job seekers’ work history and identification of potential referees. We provide job seekers with several hard copies of the template. We conducted more than 30 interviews with employers who frequently mentioned the importance of contactable references in the screening process. When asked what information they collect from references, employers listed both non-cognitive skills like motivation, reliability and work ethic as well as cognitive skills like numeracy and literacy. They are also interested in the nature of the relationship between the referee and job seeker and why the employment relationship ended. Based on this feedback, we designed a reference letter template that employers can easily fill out. Figure A.1 in the Appendix shows the

> 6Using the limited demographic information provided in ESSA, we find that age and gender are not correlated with the decision to participate. By contrast, every year of additional education increases the probability of participation by 1.6 percentage points (p-value: 0.063). Of those that agree to participate, 63.5% showed up at the labor center on the specified day. None of the socioeconomic variables predict whether participants fail to show up at the agreed time and day.

> 7The test takes about 20 minutes and was designed by the researchers. It closely follows standard entry level tests used in the hiring process by large employers in South Africa. Test scores are approximately normally distributed with a mean (median) joint numeracy and literacy score of 61% (63%). For sample questions see Figure A.3.

9
48

# A&Mendix table A2. **Chile: sources of cntral governMent expenditures**

# on PNAC (million 1986 **Us S$**

||BUDGET FROM<br>MINISTRY AF<br>ABMT|FOREIGN<br>DONATIONS|TOTAL<br>BUDGE|
|---|---|---|---|
|1978|35.0|n.a.|n.a.|
|1979|38.1|n.a.|n.a.|
|1980|27.8|n.a.|n.a.|
|1981|34.5|n.a.|n.a.|
|1982|35.9|n.a.|n.a.|
|1983|28.2|n.a.|n.a.|
|1984|35.1|10.3|45.4|
|1985|29.7|10.3|40.0|
|1986|26.1|9,.0|35.1|
|1987|38.5|3.2|41.7|
|1988|31.1|9.8|40.9|

- not including municipal expenditures

- 1986 period average exchange rate used - Ch $193.016:US $1.00

- Source: World Bank unpublished documents
|(6)|-0.083**<br>(0.040)|Untreated Only<br>3.60<br>9376<br>Yes<br>Yes<br>Yes|Yes|0.974|ajor Violent Events is<br> Events before start of|
|---|---|---|---|---|---|
|(5)|-0.052**<br>(0.025)|All<br>3.70<br>10642<br>Yes<br>Yes<br>Yes|Yes|0.977|and # M<br>or Violent <br>0.1.|
|Log Active Firms<br>(4)<br><br>-0.086**<br><br>(0.042)||Untreated Only<br>3.60<br>9376<br>Yes<br>Yes<br>Yes|Yes|0.974|of killings distribution,<br>ps all districts with Maj<br>_<_0.01, ** p_<_0.05, * p_<_|
|(3)<br>-0.057*<br>(0.032)||All<br>3.70<br>10642<br>Yes<br>Yes<br>Yes|Yes|0.976|in top 1% <br>ample dro<br>evel. *** p|
|(2)<br>-0.096***<br>(0.035)||All<br>3.70<br>10642<br>Yes<br>Yes<br>No|No|0.961|ous month <br>ated Only s<br> at district l|
|(1)<br>0.185<br>(0.184)||All<br>3.70<br>10642<br>No<br>No<br>No|No|0.002|if any previ<br>time. Untre<br>rs clustered|
|r Violent Event (=1)|Violent Events|come<br>ons<br>Es<br>inear Trends|uadratic Trends|R2|Major Violent Event =1 <br> of events in district over <br> April 2013. Standard erro|
|ajo|or|e<br>Out<br>ati<br>t F<br>FEs<br>t L|t Q|ed|ost <br>otal<br>a in|
|M|aj|pl<br>n <br>rv<br>ric<br>e <br>ric|ric|st|: P<br>g t<br>at|
|Post|# M|Sam<br>Mea<br>Obse<br>Dist<br>Tim<br>Dist|Dist|Adju|_Notes_<br>runnin<br>CDR d|

35
calorie including FAFH is then calculated as a weighted average of the average costs per calorie for FAFH and food purchased for consumption at home, where the weights are the budget shares of FAFH and food purchased for consumption at home. Using such a factor to adjust cost per calorie is also the approach used in World Bank (2007) and Silveira et al. (2007). We re-run our CBN estimation with this adjusted cost per calorie. Table 11 shows the results. The food poverty line increases by about 11 percent, to R$287, while the lower total poverty line reaches R$503.

**Table 10. Expenditures on food consumed away from home as proportion of total food expenditures**

|**Welfare decile**|**1**|**2**|**3**|**4**|**5**|**6**|**7**|**8**|**9**|**10**|
|---|---|---|---|---|---|---|---|---|---|---|
|**Share of FAFH in**|||||||||||
|**total food**|19.0%|21.2%|23.4%|24.5%|26.9%|26.7%|29.2%|30.7%|35.1%|42.8%|
|**expenditures**|||||||||||

_Source:_ Own calculations using POF 2017/18. Notes: FAFH refers to food purchased away from home.

**Table 11. Poverty lines and headcounts using 1.5 factor on food away from home**

|**Total Poverty**|**Food Poverty**|**Lower Total**|
|---|---|---|
|**Estimation**||**Poverty**|
|Parametric|R$287|R$507|
|Nonparametric|R$287|R$503|

_Source:_ Own calculations using POF 2017/18.

# Reference group

An important part for the definition of the food basket and the following calculations is the selection of the reference group. Our specification of the bottom 40 percent of the consumption per capita distribution aims to include the poor population as well as a group of households that may not be poor, but that are certainly vulnerable to fall back into poverty. The choice remains arbitrary. We hence explore how selecting another reference group would affect our findings. Figure 3 shows that, in the bottom half of the consumption distribution, the cost per calorie varies only slightly among households. Each consumption vintile’s food basket varies slightly, around R$0.004/kcal.

Following World Bank (2007), we run our CBN approach while redefining the reference group to include households that belong to the second and third consumption deciles. Table 12 shows the results. The table shows a drop in both food and total poverty lines, although their levels remain relatively close to our main results.

19
revenue side, agriculture also has an important role to play. Tax revenues in Pakistan have been stagnant for many years at about 13-14 percent of GDP.

Agriculture also plays a key role in extnal baln. The current-account deficit has remained near 5 percent of GDP over the last five years and extemal indebtedness (as a ratio to GDP) has not improved. Strong export performance, including agricultural items, has, however stabilized the current-account deficit and improved the ability to service the debt.

Agriculture is at the center if many issues in natural resource management and environmental protection and, so, sustainable development. This is because it remains the primary user of the natural resource base: land and water.

# Performance

A longer view of agriculture sector performance and past sources of growth can help assess what explains rapid growth as well as identify what sources of growth can be tapped in the future. Table I divides growth in agricultural into tree epochs (1960s, 1970s, and 1980s90s), with a different pattern of growdt at each stage. The strong growth in the 1960s was driven by greater certainty in the use of irrigation water due to an agreement with India, a productivity enhancing fertilizer-seed package, the emergence of tubewells and electrification of rural areas, and policy changes which increased the profitability of the agriculture sector.

Table 1 Growth in Ag.culture, 1960-1993.

|Period|Average Annual Growth|
|---|---|
|1959-60 to 1969-70|4.9|
|1969-70 to 1979-80|2.3|
|1979-80 to 1987-88|3.6|
|1988-89 to 1993-94|3.6|

Source: Economic Survey of Pakistn' Calculations to 1988 are taken from Gross National Product at Constant Factor Cost of 1959-60, under the old National Accounts Methodology, from the Statistical Supplemen **t** o the Economic Survey of Pakistan, I992-93. Growth is assumed to be continuously compounded. The change in the national income methodology after 1988 prevents us from presenting complete comparable figures since 1979-80. For this reason, figures are presented through to and since 1988.

2
tors. Despite the growing concern about the potential impacts of climate change, however, not much is known about the impacts of extreme weather events on incomes and poverty. Existing studies have either focused on the potential impacts of climate change on specific economic sectors at a macro-level of analysis (CEPAL, 2014) or on more micro analysis estimating the potential impacts of climate change on food security (Ervin & Gayoso de Ervin, 2019).

In this paper, we analyze to what extent weather shocks have had an effect on (labor) incomes earned and poverty in Paraguay. Towards this goal, we combine yearly household survey data from the Permanent Continuous Household Survey ( _Encuesta Permanente de Hogares Continua_ (EPHC)) with ERA5 temperature data and CHIRPS precipitation data between 2004 and 2019. We merge these datasets at the lowest administrative level possible (districts) to account for large variations in weather across the country and construct short-term weather shock variables characterized as anomalies from long-term means. Then, our empirical strategy consist of exploiting variations in weather shocks across districts and time, following closely Letta, Montalbano, and Tol (2018), Sedova and Kalkuhl (2020), and Aggarwal (2021) through pooled OLS cross-sectional regression models.

Our main findings indicate heat shocks lead to average reductions of households’ incomes of 5% in urban areas, and up to 8.8% in rural areas, over the period of study. Drought shocks show similar negative impacts on rural areas. Our results also show that short-term weather shocks are associated with increases in poverty, with heat shocks increasing poverty levels by 4.2 percentage points in rural areas, and 1.7 percentage points in urban areas, on average. Flood shocks primarily affect urban areas, increasing poverty by 1.9 percentage points, on average. The results presented in this paper also evidence the regional heterogeneity of the impacts of short-term weather shocks: while heat shocks and flooding are most detrimental in urban areas, heat shocks and droughts have the largest negative effects on rural socio-economic well-being. These findings suggest that Paraguay’s considerable poverty reduction over the past decades may be threatened in the face of climate change. Therefore, protecting the incomes of the most poor and vulnerable will become increasingly important to avoid set-backs in poverty reduction efforts and enhance resilience to future shocks.

The reminder of the paper is structured as follows. Section 2 reviews the existing literature, and Section 3 provides in-depth background information on the context of poverty and weather shocks in Paraguay. Data and methods are presented in Section 4, while Section 5 provides the results. In Section 6, we discuss the findings, and Section 7 concludes and presents some policy options.

2