rafmacalaba/datause-encoder-data huggingface dataset:
present in the work done of IRI (Hellmuth et al. 2009) and the Oxfam America R4 initiative<sup>16</sup> , Oxfam America 2013. Weather index insurance schemes based on the use of objective, transparent, weather indices that correlate well<sup>17</sup> with crop yield have been promoted by major development agencies and their partners as a way of surmounting the difficulties of traditional indemnity based insurance for small farmers (World Bank 2011). The use of weather indices as part of a risk management instrument for small farmers is discussed in various publications from these development agencies (e.g. World Bank 2011, IFAD 2011, and FAO: Hellmuth et al. 2009, Hazell et al. 2010 and Smith et al. 2009).

At the national level, the rationale for insurance is in enhancing the state’s ability to quickly respond to meet the food needs of its people following the impact of a disaster. Agriculture production in Sub‐Saharan Africa and South Asia, the two regions that have the highest exposure to food insecurity, and parts of East Asia and South America as well as the Caribbean, is predominantly small scale and rainfed. Extreme rainfall distributions (drought or flood) happen regularly with occurrence of small losses in large areas or large losses in small pockets on an almost yearly basis. However, every so often the climatic conditions are more severe and cover a larger area leading to large losses over large areas (in a country and even regionally across countries) that lead to food crisis situations at the national/regional level requiring international food aid. Impacts of climate change as currently available from global circulation models show the possibility of a more extreme distribution of rainfall, which could impact the more drought exposed countries further.

At the national level, the impacts of large‐scale droughts can be devastating and for some countries as in the case of low‐income countries in Sub‐Saharan Africa the drought risk is significant even at lower return periods. Figure 2 shows the impact of drought on Malawi’s GDP by return period of the drought event. The 1‐in‐10 year event is seen to have a negative impact of 3.5% and the 1‐in‐15 year event a negative impact of 7.2% on Malawi’s annual GDP.

> 16 R4 stands for risk reduction, risk taking, risk transfer, risk reserves.

> 17 How well the weather index correlates with crop yield and how well the weather index represents the actual weather conditions at a location which could be at some distance from the station at which the weather data is collected define the basis risk, meaning the difference between the actual risk and the modeled risk.

7
# **1. Introduction**

Recent evidence suggests that the use of imported or foreign intermediate inputs contributes positively to the growth and development of economies (Amiti and Konings, 2007; Bernard et al., 2007; Seker, 2012). This may be because foreign inputs have superior embedded technology or because certain foreign and domestic inputs are imperfect substitutes (Halpern et al., 2009; Gibson and Graciano, 2011).<sup>1</sup> However, existing evidence on the determinants and effects of foreign inputs is still relatively unexplored.

Using a repeated cross section of manufacturing firms across 26 developing countries with available data, we analyze how the percentage of a firm’s material inputs that are of foreign origin (henceforth, foreign inputs) varies with the cost of importing as measured by the World Bank’s Doing Business project. This is a first step towards understanding the connection between foreign inputs usage and trade policy design. We note that our estimation method involves regressing changes over time in import costs and foreign inputs (figure 1) and therefore it is less likely to suffer from endogeneity problems that plague pure cross-country regressions.

Our results reveal a statistically significant and economically large negative relationship between import costs and foreign inputs. For example, in Rwanda, which witnessed the largest increase in import costs from $4000 to $4990 between 2006 and 2011 in our sample, estimates suggest that the associated decline in foreign inputs equaled a large 15.8 percentage points (from 52 to 36.2 percent). We also find that the relationship between import costs and foreign inputs is non-linear, being much stronger (more negative) at relatively lower values of import costs. Hence, even countries with relatively low import costs could benefit substantially via increased use of foreign inputs from further reductions in the import costs.

> 1 For a literature review, see for example Wagner (2012).

2
# **1. Introduction and overview**

The risks associated with premature liberalization and external integration of the financial sector in emerging markets have been known at least since the documentation of the Southern Cone experience by Diaz-Alejandro (1985). However, the subprime mortgage crisis which began in 2006 in the U.S. and then morphed into the Great Recession of 2008-09 shows that financial systems even in the advanced economies are vulnerable. Notably, evidence in Philippon (2008) shows that the U.S. crisis was preceded by a massive and unprecedented expansion of the financial sector between 2002 and 2007. Philippon does not find an explanation for this expansion based on the needs of the corporate sector, although as others have pointed out, this may be because of the rise of household borrowing in connection with subprime mortgage loans combined with moral hazard and excessive risk-taking.

The point emerging from the above is that the financial sector must be assessed in terms of its impact on the growth of the real sector, which is where the social costs and benefits ultimately reside. For example, the authors of the 2010 Squam Lake Report (French et al. 2010) on fixing the U.S. financial sector note (p. 26) that ―...effective financial regulations require that politicians, and ultimately, the public, have an adequate understanding of the financial system. The political turmoil surrounding the Crisis suggests the importance of disseminating expert knowledge about finance to a broader audience ...‖ The starting point of conveying such understanding in order to gain support for regulatory reform must be an analysis of the links between the financial sector and growth in the nonfinancial sector. This paper contains such an analysis looking at 8 nonfinancial sectors in 28 countries over 1960-2005.

The analysis focuses on the symmetry/asymmetry patterns of financial deepening cycles (slower increases, more abrupt collapses). Similar questions arise regarding the boom-bust cycles triggered by financial depth cycles, measured as discrete positive/negative jumps in the growth rate of real financial sector value-added. The presence of what Rajan (2006) dubbed the ―hidden tail risk‖ manifests itself in negative skewness and high degree of kurtosis in the real growth rate of the financial sector. The asymmetries in the patterns of financial deepening are evident in the statistical analysis of higher moments (skewness, kurtosis) of financial sector growth rates. Furthermore, we find that a higher rate of financial sector growth relative to GDP raises the likelihood of future financial contractions. Philippon (2008) pointed out that such a 2
|**Model**|**Background**|**Further Analysis**|**Aim**|**Modeling approach**|**Production Function**|**Utility Function**|
|---|---|---|---|---|---|---|
|**Tirado****_et. al.,_2006**|Tirado_et. al., _(2004)|Tirado_et. al., _2006|explore the impact of increasing<br>the technical efficiency of water<br>use in the tourism sector.||||
|**Kohn, 2003**||||Heckscher - Ohlin - Samuelson<br>model|Cobb-Douglas|Simple multiplicative|
|**Briand, 2004**|||To estimate the production and<br>employment impacts of water<br>policy<br>pricing<br>on<br>the<br>development of both formal and<br>informal<br>water<br>distribution<br>segments.|Static CGE|Nested CES, 3 Level for<br>drinking water, 4 level for<br>distribution,<br>5<br>level<br>for<br>agriculture|<br> <br> <br>Linear<br>System<br>of<br>Expenditure|
|**Finoff, 2004**|||effects stochastic changes in<br>salinity levels and an initial<br>shock<br>to<br>species-population<br>levels on the ecological and<br>economic variables|Bioeconomic Model|Agents are energymaximizers||
|**Boccanfuso**<br>**_et._**<br>**_al._**<br>**2005**|**_,_**<br>extends Decaluwe (2001) by<br>introducingwater utilities||investigate on the distributional<br>impact of privatization of the<br>water utility and to isolate<br>winners and losers of following<br>privatization in Senegal|Integrated Multi-household|3 level nested CES|Cobb-Douglas|
|**Diao****_et. al.,_2005**|Diao and Roe 2000,2003||economy-wide gains from the<br>allocation of surface irrigation<br>water<br>decentralized<br>mechanism<br>for<br>achieving<br>this<br>result<br>in<br>a<br>spatially<br>heterogeneous<br>environment.|Intertemporal CGE|Available upon request||
|**Roe****_et. al._, 2005**|||Analyzing the effects of top-<br>down and bottom-up reforms on<br>irrigation water allocation.|Combines a CGE model with a<br>farm model|Homogenous of degree one and<br>non-increasingin inputs||

39
Behaghel, Luc, Bruno Crépon and Marc Gurgand (2014) “Private and Public Provision of Counseling to Job-Seekers: Evidence from a Large Controlled Experiment”, _American Economic Journal: Applied Economics_ , forthcoming.

Blundell, Richard, Monica Costas Dias, Costas Meghir, and John van Reenen (2004), “Evaluating the Employment Impact of a Mandatory Job Search Program”, _Journal of the European Economic Association_ 2(4), 569-606.

Card, David, Jochen Kluve, and Andrea Weber (2010) “Active labour market policy evaluations: A metaanalysis,” _Economic Journal_ , 120 (548), F452–F477 Labor Market Policies have Displacement Effects? Evidence from a Clustered Randomized Experiment,” _Quarterly Journal of Economics_ , 128 (2), 531–580.

Franklin, Simon (2014) “Search frictions and Urban Youth Unemployment: Evidence from an Experiment in Subsidized Transport”, Mimeo. Oxford University.

Groh, Matthew, Krishnan, Nandini, McKenzie, David, and Vishwanath, Tara (2013) “Soft Skills or Hard Cash: The Impact of Training and Wage Subsidy Programs on Female Youth Employment in Jordan” _Bread Working Paper_ No. 377.

Groh, Matthew, David McKenzie and Tara Vishwanath (2014) “Reducing Information Asymmetries in the Youth Labor Market of Jordan with Psychometrics and Skill Based Tests”, _World Bank Economic Review Papers & Proceedings_ , forthcoming _._ Horton, John (2013) “The Effects of Subsidizing Employer Search”, Mimeo. NYU Stern School of Business.

Iqbal, Farrukj, and Susan Razzaz (2008). Job Growth without Unemployment Reduction: The Experience of Jordan. World Bank.

Jensen, Robert (2012) “Do Labor Market Opportunities Affect Young Women’s Work and Family Decisions? Experimental Evidence from India,” _Quarterly Journal of Economics, ,_ 127 (2), 753–792 JLMPS (2010) Jordan Labor Market Panel Survey 2010. Economic Research Forum, Cairo, Egypt (www.erfdataportl.com).

Pallais, Amanda (2014). “Inefficient Hiring in Entry-Level Labor Markets.” Forthcoming, _American Economic Review_ .

Paunonen, Sampo and Jackson, Douglas (1996). “The Jackson Personality Inventory and the Five-Factor Model of Personality.” _Journal of Research in Personality_ . 30(1): 42-59 27
and housing improvements — affect host communities’ policy views, altruism, and interactions with refugees.<sup>2</sup> The study relates to a literature on transfers and potential negative spillover effects on non-recipients (Haushofer and Shapiro 2016, Haushofer and Shapiro 2018). But unlike other settings where transfer recipients are members of the local community, this study measures nonrecipients’ reactions to refugees — who are outsiders — receiving in-kind transfers. The closest concurrent studies to this one are Baseler et al. (2023) and Beltramo et al. (2024), both of which examine the effects of refugee assistance programs that also directly benefit host communities by, for example, granting them cash transfers. Of course, due to financial constraints, most humanitarian assistance is limited to forcibly displaced populations and not host community members, as in our setting.

Take-up of the housing assistance was moderate at 33%, and multiple factors contributed to this relatively weak first stage relationship. For one, almost a fifth of homes were deemed ineligible for assistance, typically because the implementing partner viewed the housing shelter as too precarious to support (i.e., temporary structures), and occasionally because it was determined that the residence did not need physical upgrades. There is also qualitative evidence that low take-up was at least in part due to some landlords’ reluctance to make signed legal commitments to refugees for the lease, and with the implementing partner for the necessary construction. This is a setting in which most rental contracts are informal and landlords have ample discretion over their terms and a largely free hand to evict tenants. Despite the appeal of guaranteed rent for a year plus funding for housing upgrades, some landlords preferred not to “bind” themselves to the program and the particular recipient refugee household currently residing in their property.<sup>3</sup> One of the study’s main empirical findings is that we detect no significant positive impacts of the housing assistance program for refugees along a range of pre-specified primary outcomes, with the exception of housing expenditures where there is the expected (and somewhat mechanical) drop in spending. Beyond housing expenditures, the other primary pre-specified outcomes in-

> 2We do this by surveyed neighbors but excluding landlords, who were often involved in the program.

> 3The data underlying these findings is from our implementing partner’s Integrated Assessment Shelter Analysis.

3
technologies increases the knowledge of workers.

The hypothesis that openness leads to on-the-job learning by doing through technology transfer, may be tested by relating measures of technology transfer to estimated return to experience. Technology transfer takes place either through the production of goods in less developed countries which were already produced in more developed economies, through the importation of intermediate goods or R&D spillover. R&D spillover are likely to work through imported goods from more developed countries.<sup>23</sup> This suggests to use technologically intensive imports from more developed economies as a proxy for technology transfer. But technology transfer may not only be related to imports, but also to exports. Exporting to more developed countries may require to implement strategies that increase ...rm-level e¢ ciency. In addition, contact with foreign customers is likely to create an environment of learning opportunities.

If trade leads to on-the-job human capital accumulation through technology transfer, then for less developed countries imports from or exports to non-OECD countries can be expected to have a positive e¤ect on returns to experience. The same applies to imports of technology intensive goods. Regressing the estimated returns to experience on various measures of imports and exports, such as exports and imports by trading partner (OECD versus non OECD) and imports of computers per worker yields the coe¢ cients presented in Table 9:<sup>24</sup> Two speci...cations are displayed in this table. Speci...cation (I) controls for a measure of openness and regional dummies. GDP, the share of manufacturing and GADP are added in speci...cation (II). The e¤ect on returns to home-country experience remains positive independent of the trade measure used. The coe¢ cient on computer imports is statistically highly signi...cant in both samples in speci...cation (I). The same applies to manufacturing exports.

Summarizing, these results indicate a positive and signi...cant e¤ect of openness in the home country on returns to home country experience of US immigrants. High investment rates are a signi...cant determinant of on-thejob human capital accumulation as well as governmental and institutional

> 23 For example, Coe, Helpman and Ho¤maister (1995) ...nd that total factor productivity in developing countries is positively associated with R&D expenditure abroad and that the spillover from an industrial country to a developing country are proportional to the share of the industrial country’s imports in the developing countries’gross domestic product.

> 24 Trade measures are taken from Caselli and Coleman (2001) who construct the data using information provided by Feenstra, Lipsey and Bowen (1997). For a detailed description of the data see Caselli and Coleman (2001). With the exception of log Open all variables are de...ned in per worker terms.

17
The remainder of the paper is as follows: Section 2 briefly summarizes existing literature on list randomization; Section 3 describes the list randomization question used in our study and the four surveys in which it was added; Section 4 gives our main results; and Section 5 provides discussion and conclusions.

# **2. List Randomization**

List randomization (also referred to as list experiments, the item-count technique, and the unmatched count technique) was introduced by Miller (1984) as a way of eliciting information about sensitive behaviors (in her case, illegal drug use). It has been used in a number of papers in sociology, political science, and psychology to measure incidences of sensitive behaviors as well as attitudes that might otherwise be misreported because of social desirability pressures.

The use of this method typically leads to higher reports of sensitive behaviors than is obtained through direct questioning. For example, LaBrie and Earleywine (2000) find college students to have higher incidences of having had sex without a condom, and having had sex without a ‐ condom after drinking via the list randomization method than in an anonymous self report survey; Gonzalez-Ocantos et al. (2012) use it to find higher incidences of people reporting they had been promised a gift or service in exchange for their vote in elections in Nicaragua; Tsuchiya et al. (2007) find a higher proportion of shop-lifters than by direct questioning; and Wimbush and Dalton (1997) find higher incidences of reports of employees engaging in theft. This technique has seldom been used in economics, but a recent exception is Karlan and Zinman (2012) who find microfinance clients to be more likely to report spending their loans on things other than business uses when asked via list randomization than through direct response. In contrast, actions and behaviors which have not had social stigma or illegality associated with them have resulted in similar estimates via list randomization as from direct elicitation. Examples include asking college students whether they have gotten drunk (LaBrie and Earleywine, 2000) and asking about giving blood (Tsuchiya et al, 2007).

As well as behaviors, the method has been used in a number of contexts to elicit attitudes, such as racial prejudice (Blair and Imai, 2012) and attitudes towards safety after civil conflict (Jayasuriya and Gibson, 2013). The one migration-related study we are aware of which uses this technique follows in this line of using the method to elicit attitudes. Janus (2010) uses the 4
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exposed to women in leadership roles, providing substantial evidence of the framework regarding attitudes and bias implicit in the Hoff and Stiglitz (2010).

Duflo (2005) provides an assessment of the case for political reservations for women and other historically underrepresented groups. Using evidence from India, Duflo (2005) concludes that reservations have been shown to incur a significant reallocation of public goods toward the preferred allocation of the group in power. Pande and Ford (2011) provide a more recent comprehensive review of the literature on gender quotas. They conclude that the political reservations led to a significant increase in women’s leadership and influence on policy outcomes, while noting at times more mixed evidence on some outcomes. This review also highlights the need for greater study of economic consequences.

The above studies primarily use the cross-sectional nature of the randomized reservation system to identify treatment effects. However, variation in the timing of the implementation of the 73<sup>rd</sup> Amendment was also plausibly exogenous, as noted above and further tested later in this paper. Iyer et al (2012) use this state-level variation to investigate the effects of political representation on crime against women, finding significant evidence that political empowerment resulted in greater reporting of crimes against women.

# **3.  India Manufacturing Data**

Our primary data sources are repeated cross-sectional establishment-level data from surveys of the unorganized manufacturing sector carried out by the Government of India. The data are taken from surveys conducted in fiscal years 1994, 2000, and 2005.<sup>7</sup> This section describes some key features of these data for our study, and we refer readers to Ghani et al. (2013a,b), Nataraj (2011) and Kathuria et al. (2010) for greater details and general descriptive statistics on these manufacturing surveys.

Our work mainly considers the portion of the Indian economy surveyed by the National Sample Survey Organisation (NSSO). The NSSO periodically collects information on a

> 7 In all cases, the survey was undertaken over two fiscal years (e.g., the 1994 survey was conducted during 1994-1995), but we will only refer to the initial year for simplicity. We utilize the 1989 version of the NSSO survey to check for pre-trends in women’s employment in manufacturing by state, but this dataset unfortunately lacks the key business ownership variables upon which we build our entrepreneurship metrics.

9