rafmacalaba/datause-encoder-data huggingface dataset:
_Why Infrastructure Financing Facilities Often Fall Short of Their Objectives_ _S_ hampered by regulatory restrictions (e. i. are institutional funds allowed to invest also in non-investment grade securities).

_9. Adequate Design Features of Facility._ The analysis presented also illustrates that the IFF's success was also adversely affected by micro-level issues relating to its design including inconsistent objectives, an inadequate institutional framework, and inadequate design parameters.

10. _Develop Clear and Consistent Objectives._ The cross country analysis suggests that public-sector counterparts should develop clear and consistent objectives on which to base the design of the facility as some objectives could work at cross purposes. For example, the Government may want to achieve such development objectives via the facility as expanding liquidity, lowering funding cost by offering credit enhancements, better allocating risk between the government and the private sector, developing the domestic capital market, improving the quality of service and increasing competition. However, governments will be unable to pursue all of these objectives at the same time. A better allocation of risk between the private and public sector may lead to higher risk exposure of the private sector, which in turn may reduce private resources flowing into infrastructure.<sup>4</sup> In addition, government should avoid mixing commercial and developmental objectives as instruments for the latter may feature required pricing at levels that may not allow for a market return. Moreover, to provide effective and efficient support to private participation in infrastructure on a transitional basis, the design parameters of the IFF should be consistent with the policy environment.

11. _Understand Investor Requirements._ As experience presented in the paper further reveals, to ensure that the design of the facility is offering instruments that addresses the impediments to private participation in infrastructure, the government may want to conduct a thorough demand survey. A demand or broader market survey may also provide guidance to the government on the following issues:

- to identify the nature and magnitude of the financing gap;

- the appropriateness of the fund as an instrument to support private investment and the timing of the fund;

- the design of instruments;

- the 1FF funding requirements; and

- the staffing levels and skill mix needed to manage those instruments.

12. Nevertheless, the development of such funds tends to be a complex and time consuming process, especially if contingent instruments are offered as the facility may need to build up institutional capacity. In the meantime, given that developing countries tend to be vulnerable to shocks, economic conditions may change and may adversely 4 Nevertheless, at the same time, government may have implemented a set of policy reform that improves the overall regulatory environment and allow, among other things, for cost covering tariffs. This would in turn reduce govemments' the need for the govemment to offer financial support to attract private resources into the sector.
of the headcount for 2000, by region. The figures report the percent of households falling below the household-specific poverty lines calculated by El-Laithy, Lokshin, and Banerji (2003). The second column uses the same poverty lines, but replaces the actual distribution of expenditure with the counterfactual distribution reflecting the welfare losses due to the depreciation, and the third column reports the difference between the two. For Egypt as a whole, the estimated welfare effects of the depreciation can be interpreted as raising the headcount measure of poverty by 5 percentage points. The effects are lower in the major metropolitan centers of Egypt, with poverty increasing by 2 percent from a low base. Rural areas of Egypt saw the largest absolute increase in the headcount of 6.4 and 6.7 percent in lower and upper Egypt respectively, but from a much higher base. Not surprisingly, the ranking of poverty impacts across regions is quite similar to the ranking of welfare effects across regions in Table 4. The final column of Table 5 shows the actual headcounts by region in 2005 for reference. It is interesting to note that the estimated poverty impacts of exchange-rate-induced changes in consumer prices are substantial when compared with the overall change in poverty between 2000 and 2005.

I finally consider the role of substitution effects in response to the price changes induced by the depreciation. In order to implement Equations (14) and (15) I need information on changes over time on spending on each of the 20 expenditure items. Although I have access to the 2000 and 2005 household surveys, unfortunately these are not true panels but repeated cross-sections. I therefore employ cohort techniques to estimate the changes in spending shares, and from this the substitution effects. In particular, for the 2000 and 2005 household survey I construct cohorts based on four education categories, five age categories, and seven regional categories, for a total of 140 cohorts. For each cohort I calculate the average spending shares across the 20 expenditure items in the 2000 and 2005 surveys. Using the household-level variation within each cohort in the 2000 survey, I also estimate cohort-specific income elasticities for each expenditure share. Finally, I combine these ingredients with our estimates of the depreciation-induced price changes, to estimate the substitution effect.

The results of this exercise are summarized in Figure 7, which plots the estimated direct and substitution components of the compensating variation against log total expenditure at the cohort level. The estimates of the direct effect at the cohort level 18
# **2.2 Research questions**

Our study aims to address two questions. First, can the above findings from edutainment be generalized to social media?<sup>7</sup> Theoretical arguments can be made for social media to be less or more effective than television, radio or film. On the one hand, the need for shorter clips for social media consumption may prevent users from effectively immersing in a program and identifying with characters.<sup>8</sup> The lack of a shared community viewing experience may prevent activating the social channel. Moreover, social media friends may not be a relevant group if users perceive them as too detached and unlikely to take any credible actions against VAW in their communities.

On the other hand, social media campaigns may theoretically be more effective than “offline” media. Online campaigns can be more effective in encouraging people to seek further information or take action (e.g., visit a website or donate to a social cause) as internet sites are a few clicks away. Social media usually exposes users to a larger number of friends and acquaintances, which can facilitate the spread of gender-equality norms, especially among youth. The ease with which users can publicly display their views (e.g., by posting on their Facebook walls) and share information online can help update perceptions of social norms in online communities. Online campaigns that are effective in encouraging users to publicly show their support for a social cause can potentially trigger a cascade of broader social support, as shown by online movements such as #MeToo (Levy and Mattsson, 2021).

The second question our study addresses is whether formats that deliver messaging in more implicit ways are more effective in influencing gender norms and VAW attitudes. Implicit formats such as fictional and humorous narratives could potentially reduce counterarguing, the thoughts that may dispute persuasive arguments (Benoit, 1987), and may create a safer space for audiences to consider new views.<sup>9</sup> Lab studies, mostly conducted in US colleges, show that people are more likely to remember and internalize messages when presented in a narrative format (Frank et al. 2015; Ochoa et al. 2020; Oliver et al. 2012). On the other hand, dramas could also trivialize social issues (Moyer-Gusé, 2008). Because documentaries are usually based on real-world people and situations, their “call for action” messaging could theoretically be more effective in influencing the social channel.

> 7With social media platforms engaging one in two people worldwide (Digital 2020), delivering edutainment campaigns through this medium could potentially be a scalable and cost-effective approach for reshaping gender-equality and VAW outcomes.

> 8Berg and Zia (2017) and Banerjee et al. (2019 _a_ , _b_ ) provide suggestive evidence that program impacts were mediated by program immersion and identification with characters.

> 9Lab studies indicate that audiences enjoying an entertainment program are less likely to question and rebut program messages through increased program transportation or immersion (Hall and Bracken 2011; Moyer-Gusé 2008).

6
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# **II.  Poverty 1983 – 2004/5**

Comparable estimates of poverty for the 38<sup>th</sup> , 43<sup>rd</sup> , 50<sup>th</sup> and 61<sup>st</sup> NSS rounds suggest that at the all-India level, rural poverty declined modestly from 37.2 percent to 28.4 percent between 1993/4 and 2004/5, a rate of less than 1 percentage point per year (Table 1). This is nearly the same as the decline from 46.9 to 37.2 percent that occurred during the preceding 10 years (between 1983 and 1993/4). There is little evidence of a striking acceleration of poverty reduction in rural India alongside the well-documented acceleration of economic growth in India during this period.<sup>1</sup> Table 1 also reveals that changes in poverty at the national, and even state, level mask considerable heterogeneity in the evolution of poverty across regions. Indeed, while poverty declined in most regions, it is estimated to have risen between 1993 and 2004/5 in roughly one in six of the regions considered in our analysis.

There has been a great deal of controversy surrounding the pace, and even direction, of poverty reduction during the 1990s due to problems of comparability of the 1999/00 NSS 55<sup>th</sup> round with earlier surveys.<sup>2</sup> In a precursor to this paper, Kijima and Lanjouw (2003 and 2005) proposed a number of adjustments at restoring comparability across the 50<sup>th</sup> and 55<sup>th</sup> rounds, and suggested that poverty reduction in rural areas was very modest between 1993/94 and 1999/00, a finding that was also suggested by Sen and Himanshu (2004a and 2004b). Results in these papers suggest that the bulk of poverty reduction between 1993/4 and 2004/5 is likely to have taken place in the latter half of the decade, between 1999/00 and 2004/5. This presents a conundrum, because as shown in the next section, poverty reduction in rural India has historically been closely associated with agricultural wages and the latter half of the decade was witness to a sharp deceleration in agricultural wage growth. It has led some researchers (Himanshu 2007; Dev and Ravi, 2007) to suggest that the non-farm sector may have be a key factor behind the poverty decline during the 1990s.

> 1 In a recent contribution, Deaton (2007) suggests that official statistics may be understating the rate of rural inflation during this time period with the implication that the 2004/5 poverty estimates might be understating the true incidence of poverty in that years.  His analysis suggests that the rate of poverty decline between 1993/4 and 2004/5 discussed above may thus  be overstated by  3 percentage points. 2 See the collection of papers (Deaton, 2003a, Datt, Kozel and Ravallion, 2003, Sundaram and Tendulkar, 2003) in the Economic and Political Weekly (January 25, 2003), and the update in Deaton and Kozel (2006).

5
**Table 2: Moneylender Interest Rate and Microfinance Coverage: Heteroskedastic IV Results**

||**M**<br>|**FICovera**<br>|**ge**<br>|**Informal Int**<br>|**erest Rate**<br>|
|---|---|---|---|---|---|
||**Level**|**Residual**|**Squared**|**KV1**|**KV2**|
||(1)|(2)|(3)|(4)|(5)|
|**Dummy for High MFI coverage in**|**a village**|||**25.935**<br>**(3.61)*****|**18.878**<br>**(2.42)****|
|% of household with irrigated land|0.005|-0.001||-0.349|-0.337|
||(2.74)***|(-0.166)||(6.74)***|(6.42)***|
|Distance to bank|-0.004|0.015||-0.337|-0.354|
||(0.28)|(0.458)||(1.10)|(1.19)|
|Distance to market and facilities|-0.119|-0.022||1.371|1.124|
||(4.82)***|(-0.641)||(3.01)***|(2.43)**|
|No. of survey households in the<br>village|0.000|-0.001||-0.008|-0.008|
||(0.69)|(-1.292)||(1.62)|(1.65)*|
|% of households with VGD card|0.014|0.052***|0.054***|0.332|0.365|
||(3.25)***|(5.094)|(5.049)|(4.82)***|(4.98)***|
|% of functionally landless<br>household|-0.011|-0.019*|-0.017**|-0.038|-0.065|
||(2.42)**|(-1.895)|(-2.089)|(0.46)|(0.81)|
|Upazilla Fixed Effects|Yes|Yes|No|Yes|Yes|
|Zero Stage: Heteroskedastic Probit||||||
|LR test of homoskedasticity||||||
|χ2||71.18|35.33|||
|p-value||0.00|0.00|||
|First Stage of IV Regression||||||
|**Angrist-Pischke F Statistic**||||**119.83**|**62.29**|
|**P-value**||||**0.00**|**0.00**|

* significant at 10%; ** significant at 5%; *** significant at 1% Absolute t statistics in parentheses

32
# **1. Introduction**

Despite the large theoretical and empirical literature documenting that access to international trade can be beneficial for economic development (Edwards 1993; Goldberg and Pavcnik 2016; Wacziarg and Welch 2008), there has been a rise in protectionism in discourse and measures around the world recently (Donnan 2016). This trend is also reflected in the perceptions of individuals on trade. Pavcnik (2017) shows that the share of people reporting that trade is beneficial to the economy has declined since 2002.

Consistent with these trends, recent empirical evidence points to the negative impact import competition from developing countries had on workers in developed economies (for example, see Autor, Dorn, and Hanson 2013; Balsvik, Jensen, and Salvanes 2015; Hakobyan and McLaren 2016). Meanwhile, standard trade models predict that a rise in exports from developing to developed nations would benefit workers in countries with abundant labor. In fact, recent studies show a substantial impact of exports on poverty reduction and improved labor market outcomes at the local level in China and Vietnam (Erten and Leight 2019; McCaig 2011, McCaig and Pavcnik 2018) and on poverty and inequality among states in Brazil (Castilho, Menéndez, and Sztulman 2012). Yet other empirical studies find contrasting results, including that trade liberalization does not necessarily benefit all households in developing countries and may lead to widening inequality and declining labor market outcomes (De Loecker et al. 2016; Dix-Carneiro and Kovak 2017; Erten, Leight and Tregenna 2019; Goldberg and Pavcnik 2007; Nicita 2009; Pavcnik 2017; Revenga 1997; Topalova 2010). The underlying channels through which international trade may or may not benefit individuals and regions in developing countries are not fully understood.

This paper investigates the effects of a rise in exports on poverty and inequality using a rich municipality-level data set from a developing country. Mexico is an interesting case given its lackluster performance in economic growth and poverty reduction, despite a significant trade expansion (Hanson 2010). Mexico joined the forerunner of the World Trade Organization, the General Agreement on Tariffs and Trade, in 1986 and the North American Free Trade Agreement (NAFTA) in 1994, leading to substantial tariff reductions globally and regionally, greater export orientation, and diversification away from oil. Exports as a share of gross domestic product (GDP) rose by 20 percentage points beginning in 1994, following reforms to open the economy to trade and to liberalize domestic markets. Most of Mexico’s exports— 2
# Production Networks and Firm-level Elasticities of Substitution<sup>*</sup>

Brian C. Fujiy<sup>†</sup> Devaki Ghose<sup>‡</sup> Gaurav Khanna<sup>§</sup> _Keywords:_ production networks, elasticities of substitution, shock propagation, resilience _JEL Codes:_ D57, E32, E61, F10, L14

*We thank participants at the Danish International Economics Workshop, AEA 2024, World Bank, CEPR’s Globalisation, Strategic Autonomy, and Economic Resilience in Time of Crisis, Annual Mid-Atlantic International Trade Workshop, Midwest International Economic Development Conference, STEG’s Annual Conference, IMF’s Jacques Polak Annual Research Conference, Bank of Italy’s Global Value Chains, George Washington University, and Lund University for their comments and suggestions. We thank David Baqaee, Christoph Boehm, Ana Cecilia Fieler, Banu Demir, Yuhei Miyauchi, Pablo Garriga, Andrei Levchenko, Sebnem Kalemli-Ozcan, Scott Orr, Ludovic Panon, Carolina Sanchez, Ritam Chaurey, and Sebastian Sotelo for insightful discussions. We thank Ahmed Magdy and Eli Mogel for their excellent research assistance and Sushil Khanna for guidance on the data and details on the analysis. The authors gratefully acknowledge support by the Umbrella Facility for Trade, which is funded by the governments of The Netherlands, Norway, Switzerland, Sweden and the United Kingdom, and the Research Support Budget of the World Bank. The views expressed in this paper do not represent the views of the World Bank or its partner organizations and solely represent the authors’ personal views.

†U.S. Census Bureau, brian.j.cevallos@census.gov.

- ‡The World Bank, dghose@worldbank.org.

- §University of California, San Diego, gakhanna@ucsd.edu.
**Table 4: Two Stage Least Square Estimates of the Effects of Minimum Wages on Employment and Hours Worked**

|VARIABLES|Employment<br>All<br>Employment|Working Hours<br>Covered<br>Log-hours|Working hours<br>Uncovered<br>Log-hours|
|---|---|---|---|
|Log-MW|0.113***|-0.0632|0.471***|
||(0.0317)|(0.0558)|(0.149)|
|Constant|0.383***|3.718***|1.070*|
||(0.147)|(0.224)|(0.566)|
|Observations|85,876|62,442|16,438|
|R-squared|0.163|0.340|0.167|

_Notes:_

1. *** p<0.01, ** p<0.05, * p<0.1

2. Data in all regressions are weighted using sample weights.

3. Explanatory variables in the regressions also include: years of education, age, age squared, age cubed, gender, dummies for remuneration order categories, dummies for years, and value added by broad industry.

4. The covered sector is wage-earning workers in the private sector. The uncovered sector are employers and ownaccount workers in the RO sectors wage-earning employees are covered in, as well as the unemployed who have worked before in those sectors.

5. Reported significance levels are based on robust standard errors.

In all the first-stage regressions, lagged minimum wages were positively correlated with actual minimum wages. Using a standard Hausman test for the endogeneity of the minimum wage variable in the hours equations, we find that endogeneity of the minimum wage variable is not a problem. However, for the employment equation, endogeneity remains a problem.<sup>14</sup> Thus, while we are reasonably confident that our hours results do not suffer from endogeneity bias, it is this 2SLS estimate which must be considered for reporting the impact of minimum wages on employment.

The result suggests that changes in employment in the covered sector are in fact significantly positively associated with changes in minimum wages, with a 10 percent increase in minimum wages being associated with a 1.13 percent increase in employment in the covered sector.

The elasticity of 0.113 is within the range we presented in Figure 4 above which showed a number of elasticities found for LMI countries. The elasticities presented in the figure range from a negative value of -1.3 to a positive value of 1. The result is thus in line with the existing literature which has found that increases in minimum wages have either benign or only slight employment effects.

> 14 The chi-square Hausman endogeneity test statistics are 29.95, 1.07 and 0.0046 respectively for the employment, hours worked (covered sector) and hours worked (uncovered sector) regressions. The test statistic for the employment regression suggests endogeneity at the 1 percent level of significance.

17
- 1.88 -

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**Policy Research Working Paper Series**

|**Title**|**Author**|**Date**|**Contact**<br>**for paper**|
|---|---|---|---|
|WPS1925 Half a Century of Development<br>Economics: A Review Based on<br>the_Handbook of Development_<br>_Economics_|Jean Waelbroeck|May 1998|J. Sweeney<br>31021|
|WPS1926 Do Budgets Really Matter?<br>Evidence from Public Spending<br>on Education and Health in Uganda|Emmanuel Ablo<br>Ritva Reinikka|June 1998|K. Rivera<br>34141|
|WPS1927 Revenue-productive Income Tax<br>Structures and Tax Reforms in<br>Emerging Market Economies:<br>Evidence from Bulgaria|Fareed M. A. Hassan|June 1998|A. Panton<br>85433|
|WPS1928 Combining Census and Survey Data<br>to Study Spatial Dimensions<br>of Poverty|Jesko Hentschel<br>Jean Olson Lanjouw<br>Peter Lanjouw<br>Javier Poggi|June 1998|P. Lanjouw<br>34529|
|WPS1929 A Database of World Infrastructure<br>Stocks, 1950-95|David Canning|June 1998|A. Abuzid<br>33348|
|WPS1930 The Main Determinants of Inflation in<br>Albania|Ilker Domac<br>Carlos Elbrit|June 1998|F. Lewis<br>82979|
|WPS1931 The Cost and Performance of Paid<br>Agricultural Extenion Services: The<br>Case of Agricultural Technology<br>Transfer in Nicaragua|Ariel Dinar<br>Gabriel Keynan|June 1998|F. Toppin<br>30450|
|WPS1932 Air Pollution and Health Effects:<br>A Study of Respiratory Illness<br>Among Children in Santiago, Chile|EBart D. Ostro<br>Gunnar S. Eskeland<br>1'arhan Feyzioglu<br>Jose Miguel Sanchez|June 1998|C Bernardo<br>31148|
|WPS1933 The 1997 Pension Reform in Mexico|Gloria Grandolini<br>Luis Cerda|June 1998|C. Zappala<br>87945|
|WPS1934 WTO Accession for Countries<br>in Transition|Constantine Michalopoul|os June 1998|L. Tabada<br>36896|
|WPS1935 Explaining the Increase in Inequality<br>during the Transition|Branko Milanovic|June 1998|G. Evans<br>85734|
|WPS1936 Determinants of Transient and<br>Chronic Poverty: Evidence from<br>Rural China|Jyotsna Jalan<br>Mart'n Ravallion|June 1998|P. Sader<br>33902|
|WPS1937 Aid, the Incentive Regime, and<br>Poverty Reduction|Craig Burnside<br>David Dollar|June 1998|E. Khine<br>37471|