rafmacalaba/data-use-mentions-extended huggingface dataset:
# **2. POVERTY TRENDS**

## **_Imputation_**<sup>**_11_**</sup>

Household-level poverty is calculated using imputed income from the LFS. The LFS is ideal due to the availability of regional and migrant information, but only has wage data which is insufficient to capture total income for welfare measurement. Thus total income needs to be imputed. The SILC data set can also be used to study regional poverty rates, but only at the NUTS1 level. Another disadvantage of the SILC is that spatial deflation in Turkey is only available at the NUTS2 level (LFS data), and not at the NUTS1 level since TUIK computes regional CPIs only at the NUTS2 level. Income and household characteristics from the SILC are used to produce a model to impute total income into the LFS.

The imputation model is an OLS with regionally deflated incomes at the NUTS2 level and time-invariant characteristics. Regressions are conducted using household-level data. For each year, the model specified from the SILC may vary. For every household, total household income is imputed 100 times. At the regional and comparison group level, poverty rate estimates and standard errors are computed from these 100 imputations. The international $5/day per capita 2005PPP poverty line is used. One way to interpret the poverty rates from imputed income is simply the conditional welfare based on observables.

Observed income poverty can be computed using the SILC but only at the NUTS1 level and without differentiation between the host and foreign-born populations. As a validation exercise, observed poverty computed using the SILC and imputed poverty using the LFS can be compared.

Figure 7 illustrates this comparison and shows that, at the NUTS1 level, imputed poverty rates using the LFS are very similar to observed poverty in the SILC. One caveat is that 2012 and 2013 LFS uses models computed in the 2011 SILC due to a lag in the SILC data availability and changes in the LFS survey methodology.

## **_Estimates of Poverty_**

Table 4 lists results
# **4. Conclusions**

Building on companion research using three rounds of the World Bank’s Business Pulse Surveys in South Asia, this paper quantifies the relationship between informality and firms’ investment and employment decisions. Our work suggests that informal firms face larger constraints on liquidity, access to finance, and perceived uncertainty. Accounting for multidimensionality and the margins of informality, our work suggests that _first_ , informal firms, especially those motivated by necessity and survival objectives, are both liquidity and credit constrained. _Second_ , informal firms perceive higher uncertainty in the context of the crisis. Not surprisingly, the extensive margin of informality, measured via registration or a lack of documentation, is highly correlated with the lack of credit and a higher perceived uncertainty. _Third_ , acute credit constraints and higher perceived uncertainty, especially among necessity firms, lead to a substantially lower probability of investing in digital technologies and fixed assets. Furthermore, informal firms have a lower elasticity of employment as sales begin to recover.

Our results suggest that countries with a large informal sector may need to deploy additional levers to accelerate recovery in the post-crisis period.<sup>15</sup> _First_ , a lack of access to finance by informal firms can be addressed with additional support from microfinance institutions (MFI).<sup>16</sup> At a broader scale, countries with a large informal sector should ideally focus on developing their financial markets to reduce information asymmetries and perceived risks by financial institutions. _Second_ , for dealing with uncertainty, it is important that policy makers clearly communicate the public support program in terms of the scope and time frame, to partially reduce uncertainty and its effect in delaying investment and hiring decisions. _Third_ , policies focused on generating capabilities within firms can contribute to an appreciation for investments in technologies for coping with the crisis. _Finally_ , given that the extensive margin of informality is highly correlated with outcomes on investments, policies aimed at promoting the formalization (e.g., simplified schemes for registration) if
<mark>Competitiveness, and Career Choices.”</mark> _<mark>Quarterly Journal of Economics</mark>_ <mark>129 no. 3 (2014): 1409–47.</mark> <mark>Cappelen, Alexander, John List, Anya Samek, and Bertil Tungodden. “The effect of early-childhood education on social preferences.”</mark> _Journal of Political Economy_ <mark>128, no. 7 (2020): 2739-2758.</mark> <mark>Castillo, Marco, Paul J. Ferraro, Jeffrey L. Jordan, and Ragan Petrie. “The today and tomorrow of kids: Time preferences and educational outcomes of children.”</mark> _<mark>Journal of Public Economics</mark>_ <mark>95, no. 11-12 (2011): 1377-1385.</mark> <mark>Castillo, Marco, Jeffrey L. Jordan, and Ragan Petrie. “Children’s rationality, risk attitudes and field behavior.”</mark> _<mark>European Economic Review</mark>_ <mark>102 (2018): 62-81.</mark> <mark>Castillo, Marco, Jeffrey L. Jordan, and Ragan Petrie. “Discount rates of children and high school graduation.”</mark> _<mark>The Economic Journal</mark>_ <mark>129, no. 619 (2019): 1153-1181.</mark> <mark>Castillo, Marco, John A. List, Ragan Petrie, and Anya Samek.</mark> _<mark>Detecting drivers of behavior at an early age: Evidence from a longitudinal field experiment</mark>_ <mark>. No. w28288. National Bureau of Economic Research, 2020.</mark> Chuan, Amanda, Anya Samek, and Shreemayi Samujjwala. “Does Preschool Affect Time Preferences? Evidence from a Field Experiment.
access to finance. At the same time, we show that access to finance is lower for formal firms more exposure to informal competition. As a possible mechanism underlying this result, we provide evidence that formal firms that are more exposed to informal competition have worse _expectations_ on future sales growth, which in turn are associated with fewer loan applications.

Our analysis employs WBES data for a large sample of private companies from the MENA countries. This data have two important features. First, they have a panel dimension that we exploit to account for the evolution of firm’s economic performance and characteristics across time and deal with the simultaneity bias. Second, the WBES is the only survey of firms in developing countries which provides - in addition to a large set of comparable financial variables and firms’ characteristics - information on firms’ expectations on their future performance. This is an unique type of information that we use to provide evidence of the existence of a demand channel explaining our main result.

We begin our analysis documenting the link between jobs and access to finance. Our results indicate that employment, employment growth, productivity, and wage are positively associated with loan availability for firms in MENA countries, confirming previous studies showing the beneficial effect of access to finance on job creation (Betz and Ravasan, 2016; Ayyagari et al., 2021). Next, we show that formal firms that report 1
||557,406|10,854|568,260|1%|
|Public order, safety and judicial authority||4,021,082|20,387|4,041,469|7%|
|Economic activity||4,069,536|1,355,277|5,424,813|10%|
|Environmental protection activity||92,164|54,514|146,678|0%|
|Housing and municipal economy||175,962|1,139,399|1,315,360|2%|
|Healthcare|6,260,800|866,589|141,300|7,268,689|13%|
|Physical and intellectual development system||497,119|836,333|1,333,453|2%|
|Education||2,223,457|7,457,922|9,681,380|18%|
|Socialprotection and social securitysystem|17,614,500|445,538|1,003,173|19,063,211|35%|
|**Total**|**23,875,300**|**17,413,803**|**13,260,779**|**54,549,881**|**100%**|
|healthcare % of GG expenditure|86.1%|11.9%|1.9%|100.0%||
|education % of GG expenditure||23.0%|77.0%|100.0%||

Source: Moldova BOOST data.

3 This section was prepared by Irina Capita.

> 4 The analysis relies on two BOOST data sets for Moldova – the core BOOST database available on the Ministry’s of Finance website, available at <u>https://mf
not provide information on the actual number of exporting firms. More specifically, we have (for instance) used the number of 6-digit HS product groups traded within a 3-digit ISIC sector as a measure of the extensive margin of countries exports. This could potentially bias the relative contribution of the intensive and extensive margins since the mapping between products and firms is unlikely to be one-to-one.

In what follows, we re-examine our results using a more granular trade dataset – the World Bank’s Exporter Dynamics Database (EDD). The advantage of EDD is that it provides information on the actual number of exporting firms as well as export sales per exporter, which allows us to capture the extensive and intensive margins of exports more precisely.

The results are reported in Table 8. Results show that poor institutions restrict firm entry into foreign market as well as constrain the scale of firms’ sales in foreign markets. Despite the fact that our analysis relies on a relatively smaller set of countries, our results reaffirm our earlier findings.

20
Whenever available, we follow the recommendation in McKenzie (2011) and control for the baseline value of our dependent variable and run an Analysis of Covariance (ANCOVA) specification. In addition, all specifications include strata dummies and a survey wave dummy since our follow‐up survey was conducted over two waves.<sup>10</sup>

# _V.IV. Evaluation Results – Effects on Business and Financial Knowledge and Perceptions_

In order to assess the effect of the training on business and financial knowledge, we first examine the results from the exit test that participants filled out at the end of the training. This test includes the same eight business and financial knowledge questions as the baseline survey. Results from this exit test are only available for entrepreneurs who attended the training and thus cannot be compared to a randomly chosen control group. However, comparing exit test results to baseline answers provides a first indication of whether participants improved their business and financial knowledge after the training.

Panel A in Table 5 shows the fraction of respondents who answered each question correctly, at baseline and during the exit test. The fraction of correct answers during the exit test is significantly higher than at baseline for three out of the eight questions. Somewhat surprisingly, respondents also did significantly worse during the exit test in answering two out of the eight

> 10 The second wave was necessary as the response rate was initially very low. This initial non‐response is not correlated with treatment.

18
- the larger the cross price elasticity of demand for private and public services (eVb in the first case with complete substitutability assumed in the second),

- the larger the elasticity of supply of private services (es)

We will review the evidence on each of these in turn.

_The smaller the overall elasticity of demandfor services, the smaller the impact ofpublic_ _spending._ The elasticity of demand may well be the crux of the matter. Economists tend to shy away from discussions of "need" since this is not directly observable and is emotionally charged, but if an individual "needs" something, she or he is likely to buy it over a large range of circumstances. If income falls or prices rises, consumption of a "needed" good will be protected, and the adjustment will be greater with regard to other uses of money and time.

Since we assume that necessary health services (or at the very least those that alleviate unpleasant symptoms) are highly valued by individuals, one might assume that demand for them would be fairly insensitive to circumstances such as price or availability. Therefore, for those health services which are a matter of life or death, whose presence or absence would have the greatest impact on mortality statistics, one should expect low price elasticities of demand. To the extent that severe symptoms are associated with health problems for which the impact of clinical care will be greatest, these are the problems which are likely to be treated more or less successfully, regardless of the public presence.

Indeed, in China (Cretin, 1992, 1996), Indonesia (Gertler and Molyneaux, 1995) and in the United States (Manning, et al, 1987, Newhouse, 1995), studies confirm that the demand for treatment of serious conditions is less elastic than for less serious conditions. Market failures associated with treatment of serious problems are likely to manifest themselves in ways other than bad health. For example, people may be overcharged, service may be 32
for service sector and smaller firms. This implies that the existing literature focusing exclusively on net changes in FDI is missing important aspects of the spillover process.

# **5 Conclusion**

One of the prime reasons governments aim to attract foreign investment is the belief that, by bringing in new technologies, ways of doing business, and global connections, multinationals will increase the productivity, employment, and investment of local firms. Although there is a large body of evidence supporting these effects, heretofore no one has investigated whether these effects are persistent learning spillovers, remaining after the foreign firm disinvests, or transitory leaning effects, meaning that in order to maintain the spillover it is necessary to prevent exit. We fill this gap using Jordanian firm level data during a period of both entry and exit by foreign firms. On the whole, we find notable asymmetries between entry and exit of foreign firms, with the estimates indicating a significantly transitory nature of FDI

> 35F-stat(1,2175)=6.21, P-value=0.01.

22
**Figure 3: Changing Distribution of Establishments**

<!-- Start of picture text --> Panel A<br>Change in Share of Total Establishments and<br>Employment by Size Class, 1993-2007<br>0.08 Establishments<br>0.06 Employment 5.3% 5.7%<br>0.04 3.5%<br>1.9%<br>0.02<br>0<br>-0.5%<br>-0.02<br>-1.7%<br>-2.2%<br>-0.04 -2.7% -3.2%<br>-0.06<br>-6.0%<br>-0.08<br>UltraMicro (5-9 Micro (10-19 Small (20-39 Medium (40-99 Large (100+<br>employees) employees) employees) employees) employees)<br>Source: Sri Lanka Annual Survey of Industries.<br><!-- End of picture text -->

# **Panel C**

<!-- Start of picture text --> Total EPZ employment, Sri Lanka 1983-2003<br><!-- End of picture text --> <!-- Start of picture text --> 120,000<br>104,237<br>100,000 91,404<br>84,058<br>80,000<br>60,000<br>46,104<br>40,000<br>24,093<br>20,000<br>0<br>1983 1988 1993 1998 2003<br>Source: Aggarwal, Aradhna . (2005) "PERFORMANCE OF EXPORT PROCESSING ZONES:A COMPARATIVE<br>ANALYSIS OF INDIA, SRI LANKA AND BANGLADESH," WORKING PAPER NO. 155, ICRIER Working
Policy Research Working Paper 8607

# **Abstract**

This paper examines the patterns and economic effects of foreign direct investment across the Belt and Road Initiative countries and assesses the potential role of the initiative in shaping the patterns and effects. Exploring cross-country bilateral transportation cost and foreign investment data, the analysis shows that, by reducing overall travel times and transportation costs, the proposed Belt and Road Initiative transportation network can pave the way for additional investments and increased growth in gross domestic product. But the magnitude of the effect varies significantly across source and destination countries. Aggregate foreign direct investment in Belt and Road Initiative countries is predicted to increase by around 5 percent, with regions such as Sub-Saharan Africa and East Asia and Pacific seeing greater potential gains. The increase in foreign direct investment can exert a positive effect on GDP, trade, and employment growth, especially for lower-income countries.

This paper is a product of the Macroeconomics, Trade and Investment Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/research. The authors may be contacted at xchen@gwu.edu.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
2014 and are drawn from the Penn World Table version 9.0.

The figure shows that entry barriers are sizable in the least developed economies and decrease to roughly zero in the most advanced ones. The model backs out mild entry subsidies for Latvia, Spain, and Italy, which are the countries that lie above the 45-degree line in the left panel of Figure 3.

As a first attempt to give meaning to the magnitudes, Figure 5 plots the

> 30Notice from Figure 3 that countries for which the average size under idiosyncratic distortions only lie above the 45-degree line (Latvia, Spain, Italy), the model will back out a negative value of the entry barrier (i.e., an entry subsidy).

36
# **7. Changes in support for education reforms over time**

We next investigate whether the regularities we uncover by analyzing the sample of LiTS 2023 existed in the earlier rounds of the survey.<sup>10</sup> Expectations of future mobility or support for longterm reforms may have fallen in the wake of the COVID-19 pandemic, which had profound and long-lasting impacts on economic activity and household welfare (World Bank 2022). We use data from the 2010 and 2016 rounds of the LiTS to examine the stability of the linkages between expectations of mobility and support for education reforms over time.

The 2010 and 2016 survey rounds offer two contrasting data points. Like the 2023 round, the 2010 round was conducted in the wake of the Global Financial Crisis and the European debt crisis of 2009/10. In contrast, the 2016 data were collected during the period of relative economic stability in the region.

Table 5 presents estimations for three rounds of the LiTS (2010, 2016, and 2023).<sup>11</sup> The first three sets of results demonstrate that, as in 2023, respondents with more optimistic expectations about their economic mobility were more likely to support tax-financed education reforms in 2010 and 2016. The strength of this relationship doubled from 0.007 in 2010 to 0.014 in 2016, remaining virtually unchanged in 2023. The effect on support for reforms of expectations of intergenerational mobility increased from 0.054 in 2010 to 0.073 in 2016 and decreased to 0.041 in 2023. In all three survey rounds, beliefs about the fairness of the underlying economic environment and attitudes toward risk remain significant correlates of support for tax-financed education reforms.

Two findings emerge from these intertemporal comparisons. First, the positive association between intra- and intergenerational expectations of upward mobility persists for over a decade and during periods of economic turmoil and relative calm. Second, the relationship between

> 10 The Chow (1960) test on structural break indicates that for all pairwise comparisons of
# <u>7) Conclusion</u>

This paper presents a systematic methodology to evaluate systems of housing subsidies. The methodology is applied to the system of housing subsidies prevailing in Morocco in 1995 and 2002. The various parts of the housing subsidy system are described, and rated along public finance criteria. The framework used here provides a synthetic overview of the housing subsidy system of Morocco. It may be used to compare the Moroccan system to those of similar countries. To illustrate this possibility, Figure 10 presents some of the results in a different manner.

<u>Figure 10 : Expenditures on Housing Subsidies by Type – comparison 1995-2002</u> <!-- Start of picture text --> Subsidies amounts by degree of Subsidies amounts by degree of targeting<br>transparency<br>Very Good<br>Very Good<br>Good<br>Good<br>Fair<br>Fair<br>Poor Poor<br>Very Poor Very Poor<br>0 1000 2000 3000 4000 5000 0 1000 2000 3000 4000 5000<br>Amount in 2004 (Mdhs) Amount in 2004 (Mdhs)<br>Subsidies amounts by degree of Subsidies amounts by degree of<br>efficiency sustainablility<br>Very Good Very Good<br>Good Good<br>Fair Fair<br>Poor<br>Poor<br>Very Poor<br>Very Poor<br>0 1000 2000 3000 4000<br>0 1000 2000 3000 4000<br>Amount in 2004 (Mdhs)<br>Amount in 2004 (Mdhs)<br>Targeting<br>Transparency<br>Efficiency<br>Sustainability<br><!-- End of picture text --> The paper shows that the most visible subsidies have been neither the most inefficient nor the most resource consuming for the state. Examination of changes since 1995 shows that while the most visible subsidies have received nearly all the attention, large invisible subsidies remain
<br>Share of mfg. 35.2<br>35.0 employmentShare of mfg. exports 31.1 33.2 12<br>30.0 27.8 10.9 28.8 10<br>25.0 8.9 11.6 9.3 8<br>20.0<br>6<br>15.0<br>10.0 8.0 5.2 4<br>3.7<br>5.0 2<br>0.0 0<br>1983 1986 1991 1995 1999 2003<br>Note: Exports share shows data for closest available year.<br>Source: Aggarwal, Aradhna . (2005) "PERFORMANCE OF EXPORT PROCESSING ZONES:A COMPARATIVE<br>ANALYSIS OF INDIA, SRI LANKA AND BANGLADESH," WORKING PAPER NO. 155, ICRIER Working Paper Series.<br><!-- End of picture text -->
Second, important differences exist between investor types. For all investor classes – apart from on-grid – policy and regulatory risk is the most important risk category. For ongrid investors, in turn, power sector context risk is the most important risk category, potentially because the future expansion of the power sector determines to a large extent the investment opportunities that arise and retroactive changes to expansion plans may pose a substantial risk. International investors assign more weight to country-context risk than domestic investors, potentially due to better local connections.

Third, there are striking differences between segments of the power sector. Investors perceive three segments as ‘ready’ for private solutions in Sub-Saharan Africa: power generation, off-grid electrification, and mini-grids. And when asked about the most attractive markets for investments over a three-year time horizon, respondents ranked nine countries as ‘positive’ on average: Côte d’Ivoire, Kenya, Mozambique, Nigeria, Rwanda, Senegal, South Africa, Uganda, and Zambia.

Fourth, besides understanding investors’ and financiers’ risk perception, a central motivation for the survey was to ‘reality-check’ existing, data-based assessments of countries’ readiness for investment. We find that survey respondents’ perception of countries’ readiness correlates very well with RISE 2017 scores (R2 of 0.47 for a sample of 35 countries). A similar picture emerges for the Power Sector Reform Index (R2 of 0.37 for a sample of 35 countries). Further disaggregating the RISE scores into its grid and off-grid components shows that they also correlate well with the assessment of the respective investor classes. Particularly the following components of the index show a high correlation with the subjective experience of off-grid investors: existence of an electrification plan, consumer affordability of electricity, and the existence of a framework for stand-alone systems. For grid-connected renewable energy particularly clear network connection procedures, carbon pricing and regulatory support for renewable energy are well corelated with the perception of investors.

In sum, despite many challenges, the survey underscores that past experience of power sector investments