rafmacalaba/data-use-mentions-extended huggingface dataset:
# 5. Conclusion and Policy Implications

In this paper, we discussed the incidence of shocks in Sudan by combing two household survey datasets collected in 2009 and 2014/15. By combining both rounds of data, we were able to highlight the main shocks affecting Sudanese households, the coping strategies available to and used by these households as the heterogeneity in the incidence of shocks across space (rural/urban, states, and so on), and household attributes such as livelihoods and poverty status. Drawing insights from these descriptions (such as the type and intensity of coping strategies used, the category of households mostly affected by shocks), we profile households who are likely to be resilient or vulnerable to shocks.

In the second part of the paper, we used the latest round of the data to estimate the impact of shocks on the welfare of Sudanese households. Since the impact of shocks is likely to vary across specific types of shocks and across indicators of household welfare, we consider this multidimensionality in our analysis. We also consider the heterogeneity in the impact of shocks across households distinguished by space, livelihood, use of coping mechanisms, and access to credit and informal systems of support.

The results indicate that poor agricultural rural households are most exposed to idiosyncratic shocks in general and agricultural-related shocks such as crop or livestock loss. Most of these households rely on assistance provided by family/friends, NGOs, or the government as well as on selling their assets or dissaving to cope with shocks. The fact that these strategies may be insufficient to fully mitigate the impact of shocks and enable households to escape poverty shows the need for social protection programs to reduce vulnerability and build resilience.

In terms of the impact of shocks, weather-related shocks such as floods/droughts have the largest negative impact on household welfare. On average, households affected by floods/droughts experience a 5.3 percent decrease in consumption per capita relative to those not affected by shocks. They also experience a significant decrease in their assets and are more likely
# **Job Training and Job Search Assistance Policies in Developing Countries**<sup>**#**</sup>

Eliana Carranza and David McKenzie _Keywords:_ Job training; Job search assistance; Active labor market policies. _JEL Classification codes:_ J22, J23, J24, J64, M53, O12, O15.

> # This paper is forthcoming in the Journal of Economic Perspectives. We are grateful to the editors, Heidi Williams, Erik Hurst, Nina Pavcnik, and Timothy Taylor, for their useful comments and their help in improving this piece. We thank Yves Perardel for providing us with tabulations from the Albania and Romania labor force surveys. - Computational reproducibility verified by DIME Analytics https://doi.org/10.60572/hm2r <u>nj04.</u>
<mark>Bils, Klenow, and Ruane</mark> (2020) (henceforth BKR) propose a methodology that exploits the panel structure of the data to correct for potential measurement error. The authors build on the HK approach and allow for additive<sup>5</sup> measurement error in revenues and intermediate inputs. When measurement error is additive but _i.i.d_ . over time, the levels and first differences of revenue relative to inputs provide independent signals of the true dispersion in marginal revenue products. Hence, by taking the covariance between first differences and levels of average revenue products, one could estimate the variance of the true marginal products, which captures resource misallocation within a narrowly defined industry.

We apply both HK and BKR frameworks, highlighting the differences in estimation driven by accounting for measurement error. We rely on firm-level data available from three developing Southeast Asian countries: Indonesia, Malaysia, and Vietnam. These three large and diverse economies are considered to have good panel firm-level data. Yet, results indicate that measurement error may play an important role, and accounting for it can substantially affect the extent of estimated misallocation in these economies.

> 4As acknowledged by HK, their approach relies on restrictive assumptions such as CES aggregation of differentiated products within a narrowly defined sector (allowing to derive TFPQ from revenue data in the absence of information on input and output quantities), and hence constant mark-ups within the same sectors. Under these conditions, any variation in TFPR is attributable to resource misallocation.

> 5 Assuming additive rather than multiplicative measurement error yields more conservative estimates.

4
# **2 Context and Transit Infrastructure in Amman**

Jordan is an upper middle-income economy, with GDP per capita of USD4,400 in 2021. Its capital and economic hub, Amman, is a primate city, hosting 42 percent of the national population (3.7 million people in the latest 2015 census).

Amman has been continually inhabited since the 8th century BC, but its population has grown exponentially in the past century, from just 5,000 in 1906 to 1.8 million by 1999, and over 4 million today (Ababsa and Ahmad (2020)). This growth was driven in part by large successive waves of refugees from fragile regional neighbors, most recently from the war in the Syrian Arab Republic.

Its role as a safe harbor has spurred Amman to become an important regional hub for banking, business, and tourism, but has also put urban services and labor markets under intense strain, as populations have soared almost overnight during waves of refugees crises. Most recently, at the height of the Syrian refugee crisis, water demand rose by 40 percent and unemployment by 30 percent (100 Resilient Cities, 2017).

A hilly topography, population pressures, and insufficient investment in public transport have exacerbated traffic congestion in Amman in recent years. The city is built around nineteen hills, forcing a reliance on bridges or tunnels to connect many major city roads. The density of buildings, population, and cultural heritage sites has also limited the scope for road widening as the population has boomed. In response, the Greater Amman Municipality (GAM) began constructing a Bus Rapid Transit (BRT) system in 2015, to improve the efficiency of the road network. The first BRT routes were opened in 2021 and 2022, with a third (connecting Amman to Zarqa) expected to open in 2023.

4
The effect of input tariff reductions on firms’ technology choice is heterogeneous across firms depending on their initial productivity level _φ_ . Proposition 2 shows that the high-technology productivity cutoff _φ_<sup>_∗_</sup> _h_<sup>decreases with input tariff reductions.Figure 1 illustrates the impact of input-trade liberaliza-</sup> tion on firms’ technology choice for firms with different productivity levels. Input tariff cuts reduce the high-technology productivity cutoff, allowing the most productive firms producing with low-domestic technology before input-trade liberalization to upgrade their technology embodied in imported capital goods ( _φ_<sup>_∗_</sup> _h_<sup>_′<φ<φ∗_</sup> _h_<sup>).Thesefirmswillexperienceanincreaseintheexpectedprofitsofhigh-</sup> technology, due to input tariff reductions, that allows them to cover the fixed technology adoption costs.

**_Testable implication 2:_** _The effect of input-trade liberalization is heterogeneous across firms. Firms that will benefit from input tariff cuts to upgrade foreign technology embodied in imported capital goods are firms in the middle range of the productivity distribution._

In the following sections, we test these empirical implications using the episode of India’s trade liberalization at the beginning of the 1990s.

# _V. EMPIRICAL ANALYSIS_

# _Data_

The Indian firm-level dataset is compiled from the Prowess database by the Centre for Monitoring the Indian Economy (CMIE).<sup>21</sup> This database contains information from the income statements and balance sheets of listed companies comprising more than 70 percent of the economic activity in the organized industrial sector of India. Collectively, the companies covered in Prowess account for 75 percent of all corporate taxes collected by the Government of India. The database is thus representative of large and

> 21The CMIE is an independent economic center of India that provides services of primary data collection through analytics and forecasting. Further information can be found at http://www.cmie.com/.

24
technologies are often inaccessible to smaller firms or those more severely exposed to credit restrictions. Infrastructure failures and credit limitations therefore interact in constraining firms’ development, both by making existing investments less productive and by discouraging new ones.

In this paper, we use a sample of 46,606 firms across 87 countries covering the period 2002-2006 to analyze the behavior of firms facing both infrastructure and financing constraints. In particular, our objective is to understand under which conditions they decide to invest in their own generating capacity, and how this decision is affected by the above mentioned constraints and their interactions with firm- and sector-level characteristics. The answers to these questions are important because they condition the policies towards industrial development and, in particular, the way policy makers in different environments should prioritize measures related to credit limitations versus those addressing investment in infrastructure.

A number of papers have documented the burden imposed on developing countries’ firms by an erratic, low quality supply of electricity. Early contributions include Lee, Anas and Oh (1996) and Lee, Anas, Verma and Murray (1996)—both of which use data from Nigeria, Indonesia and Thailand. Lee, Anas and Oh (1996) document the extent and incidence of public infrastructure deficiencies, the response of private entrepreneurs in terms of investment in private infrastructure and the private cost of generation. They conclude that the private costs of infrastructure deficiencies are substantial and that the burdens fall disproportionately on smaller firms, while pointing out large differences across these three countries, linked in particular to the regulatory environment. In Indonesia and Thailand, the opening up of infrastructure markets to private providers and the possibility of shared production appears to ease constraints on all categories of firms and to improve the reliability of service flows.

Lee, Anas, Verma and Murray (1996) develop a model of the firm in which electricity is produced internally, with scale economies to explain why firms supplement their purchases of publicly produced electricity with electricity produced internally (a practice that is prevalent in Nigeria, common in Indonesia
There continue to be a number of different risk factors for infant mortality. However, these risk factors have remained relatively constant over time, with male children more likely to die early than female children, a common pattern throughout the world due to genetic factors (Hill & Upchurch, 1995). Children from poorer and uneducated households and living in rural areas are also more likely to die early in life and there are substantial regional disparities (annex, Table 1).

# 4.2.2 Nutrition

In addition to facing different chances of early health care and even early death, children face unequal chances of healthy growth and nutrition depending on their backgrounds. Table 2, in the annex, presents the full set of relationships between nutrition and children’s background. Notably, there are substantial disparities in nutrition by wealth (Figure 6). As of 2011, 28 percent of the poorest children were stunted compared to 7 percent of the richest. The poorest children have also made the least progress over time; they have had relatively lower reductions in their chances of being stunted. In addition to differences by wealth, there are substantial disparities— depending on where children live and their parents’ education—for stunting and other nutrition outcomes.

**Figure 6. Stunting by Wealth Quintile and Year (Percentages)**

<!-- Start of picture text --> 100<br>90<br>80<br>70<br>60<br>50 2003/4<br>40 35 2011<br>28<br>30 25<br>20<br>20 16 16 15<br>10<br>7 7<br>10<br>0<br>Poorest Poorer Middle Richer Richest<br>Percentage<br><!-- End of picture text --> _Source:_ Authors’ calculations based on DHS 2003/04 and ENPSF 2011.

Location acutely affects children’s chances of living in a household
# 1. **Introduction**

-- There are increasing fears that trade reform -- and globalization more generally will increase the uncertainty faced by the average worker, particularly those with fewer skills. As argued by Rodrik (1997), the increased competitiveness of product markets and the greater access to foreign inputs have led to a more elastic demand for workers. This leads to greater volatility in the labor market since bad shocks to output translate to larger impacts on wages and employmen **t** han formerly was the case. Further, the increased elasticity for unskilled workers has also been posited as contributing to the increase in wage dispersion observed with liberalization, and particularly the relative worsening of unskilled relative to skilled workers.

In the "North", a considerabl **e** mpirica **l** iterature has been devoted to the study of the effects of increased imports of manufacturing goods from third world countries on the increasing levels of wage inequality and unemployment of the United States and Europe.' On the particular issue of demand elasticities, Slaughter (1997) estimated labor demand elasticities for U.S. manufacturing industries and found that from 1960 through 1990 the demand for production labor did become more elastic in most industries although it is not clear, whether increased trade was the cause.

Among LDCs the literature is almost as thin. Estimating static demand equations using micro-panel data from Turkey, Chinoy, Krishna and Mitra (1999) find no impact of ' Although conflicting results have been obtained, standard studies of factor content indicate that trade accounts for 10 to 20 percent of the fall in demand for unskilled labor (Freeman, 1995: 25). Thus, it has been argued that skill-biased technological change can explain most of the shift in demand away from unskilled towards skilled labor, at least in the U.S. manufacturing industries (Berman, Bound and Griliches, 1994).

1
/year|124.5||—|141|70.6|
|Firms’ reliance on own generator|% consumption|21||6.7|<br>24.7|11|
|Firms’ value lost due to power outages|% sales|6||4.3|<br>5.0|2|
|Delay in obtaining an electrical connection|Days|41||9.4|<br>—|12|
|Collection ratio|% billings|93|—|98.8|<br>100|100|
|System losses|% production|24|—|21.5|<br>22.5|20|
|Cost-recovery ratio|% total cost|89|—|58.3|<br>74|85|
|Total hidden costs as % of revenue|%|68|—|90|52|6|
|Effective power tariffs ()||**Senegal**|Predom<br>hydro ge|inantly<br>neration|Predominantly<br>thermal generation|<br>Other<br>developing<br>regions|
|Residential at 100 kWh/month|US cents/kWh|23.8|10|.7|15.7||
|Commercial at 900 kWh/month|US cents/kWh|22.8|12|.9|19.0||
|Industrial at 100 kVA|US cents/kWh|15.8|9.|3|13.0|5.0–10.0|
|Average tariff|US cents/kWh|22.7|—||17.0||

_Source:_ Eberhard and others 2008. Other sources include access data coming from the Demographic and Health Surveys 1996 and 2001; utility data from the AICD electricity database (www.infrastructureafrica.org/aicd/tools/data)
Policy Research Working Paper 10901

# **Abstract**

This paper presents an evaluation of a tax enforcement program conducted in Indonesia where officials from the tax authority visited properties to engage directly with owners about their property tax obligations. Through these visits, auditors explained outstanding debts and payment processes, aiming to improve tax compliance and revenue collection. The paper uses an administrative data set and a new set of machine learning–based techniques to assess the program’s effectiveness. The program was responsible for increasing tax compliance on the extensive margin by 4.3 percent and on the intensive margin by 5.1 percent in the first year it was implemented. These effects are particularly strong as they persist in the following period. The findings show that the visited properties had better compliance history, lower value, smaller area, and were more likely to have some construction on them. A key finding from the analysis is that higher-value properties are less sensitive to the visits. In other words, if a data-driven tax-enforcement strategy is to be applied, then it may focus resources on enforcing taxation at the poorest part of the population in this case. This opens up the discussion of the distributional consequences of an algorithm-based enforcement strategy, which is increasingly important as machine learning techniques are used by tax authorities.

This paper is a product of the Governance 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/prwp. The authors may be contacted at paulo.antonacci@duke.edu and mchattha@worldbank.org.

_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
The e¤ects of ...scal policy, thus, show up immediately in interest rates and other ...nancial variables. Thus, it is argued that such models su¤er from the inability to recover the ‘true’structural shock given the absence of news on future government spending. This has been termed the ‘anticipation’or ‘non fundamentalness problem’.<sup>15</sup> As a consequence it can be the case that the estimated innovations of a VAR are such only with respect to the information set of the practitioner, but not of the private sector. The implication being that government spending shocks may be misestimated. One way in which this problem could be overcome is by including observations on the present value of government spending forecasts directly in the speci...cation. Such data is currently lacking for Malaysia. However, Perotti (2011) has shown how even without the exclusion of an expectations term the estimates from structural models need not be unduly biased.

Perotti (2005), based on data for a group of OECD countries, has shown that the identi...cation scheme and choice of variables in the speci...cation outlined should provide unpredictable government spending shocks. It is worth pointing out that whether ...scal shocks are truly anticipated or not matter only if anticipated and unanticipated ...scal policy actions have di¤erent e¤ects. There is currently little agreement on this issue. Anticipation e¤ects are unlikely to undermine the central point of this paper, which is to examine the size of the changes in ...scal multipliers given shifts in economic conditions. That being whilst anticipated ...scal policy might bias the estimated impulse response functions, it is not clear whether and why such e¤ects change over the cycle.

In addition to the three baseline variables - government spending, taxes and output - in the ...scal policy literature real private consumption and an interest rate measure
Laeven, L., & Valencia, F. (2013). Systemic Banking Crises Database: An Update. IMF Economic Review, 61, 225–270. https://doi.org/10.5089/9781475505054.001 Ong, L. L. (2014). A guide to IMF stress testing. International Monetary Fund. https://doi.org/10.5089/9781484368589.071 Ong, L. L., Maino, R., & Duma, N. (2010). Into the great unknown: Stress testing with weak data. IMF Working Papers (WP/10/282). International Monetary Fund. https://doi.org/10.5089/9781455210893.001 Reinhart, C. M. (2021a). From health crisis to financial distress. World Bank Policy Research Working Paper (No. 9616). The World Bank. http://hdl.handle.net/10986/35411 Reinhart, C. M. (2021b). The quiet financial crisis. Project Syndicate. https://www.projectsyndicate.org/onpoint/covid19-balance-sheets-quiet-financial-crisis-by-carmen-reinhart-202101?a_la=english&a_d=5ff70aa06140ad371c66e00b&a_m=&a_a=click&a_s=&a_p=%2Fcolumnist%2Fca rmen-reinhart&a_li=covid19-balance-sheets-quiet-financial Reinhart, C. M., & Rogoff, K. S. (2013). Banking crises: An equal opportunity menace. Journal of Banking and Finance, 37(11), 4557–4573. https://doi.org/10.1016/j.jbankfin.2013.03.005 Yuuki, I., Will, K., Ulf, L., & Christian, S. (2021). Covid-19 and bank resilience: where do we. BIS Bulletin (No. 44). Bank for International Settlements. https://www.bis.org/publ/bisbull44.pdf World Bank (2021). Global Economic Prospects
The importance of legal knowledge is reinforced by the significance and magnitude of the coefficient of our knowledge index for short-term soil conservation. An increase of a household’s legal knowledge by one element would, according to the coefficients, result in an increase in the propensity to undertake soil conservation that is equivalent to increasing the length of possession by more than 10 years the head’s level of education by more than 3 years. In addition to being significant, the length of time for which the plot has been held by the household has the expected positive sign. The rather modest size of the coefficient suggests that long possession has little potential to improve what are essentially defective rights. Results are similar for short-term investments with the exception of a smaller negative coefficient on distance to the house and flat topography, and lack of significance of the land quality variable and steeply sloped land. Consistent with the limited visibility of the fruits of short-term investment, we find little evidence of transferability on increasing such activity, further reinforcing the importance of legal knowledge and, by implication, measures of dissemination that aim to increase such knowledge, on the way in which land is used. In fact, the _χ_<sup>_2_</sup> test statistic rejects equality of the coefficients on both variables, suggesting that, as far as short term investments in soil management are concerned, knowledge of the law matters more than having transfer rights to the land.

Household characteristics that increase farmer’s propensity to invest include the level of education which is likely to improve understanding of the underlying relationships and marketing of the products from such investment, household size and the associated availability of labor for undertaking the investment, and, somewhat surprisingly, a dummy indicating that the household is headed by a female. Higher levels of household assets in the past have no appreciable impact on investments in soil fertility but reduce the propensity to plant trees, pointing towards a substitution effect between land-attached and other productive assets.

# **4.2 Productivity determinants**
# **Estimating a Poverty Line for Brazil Based on the 2017/18 Household Budget Survey**<sup>**+**</sup>

Gabriel Lara Ibarra _The World Bank_ Anna Luisa Paffhausen _The World Bank_ Daniel Duque

## **JEL: I32**

**Keywords:** poverty lines; food poverty line; basic needs; household budget survey; Brazil

+ We would like to thank Dean Joliffe, Aziz Atamanov, Nobuo Yoshida, Emmanuel Skoufias, Liliana Sousa, Pedro H. G. Ferreira de Souza, Leonardo Oliveira, and colleagues from the Citizenship Ministry in Brazil for their helpful comments and suggestions to improve this study. All errors are our own.