rafmacalaba/data-use-mentions-extended huggingface dataset:
. Political stability, rule of law, and regulatory quality indicators were obtained from the World Bank Governance Indicators database <u>(http://www.govindicators.org) from indexes constructed by Kaufmann et al (2009).</u> Data on government consumption as a share of GDP and annual value of imports and exports as a share of GDP were obtained from Penn World Tables (Heston, Summers and Aten (2009)). We construct de-facto financial openness measures using the updated and extended version of the

> 1 As Timmer and de Vries (2007) point out, some activities in government services are nevertheless traded through markets. For example many personal services, but also private education and health services should be part of ―market services‖. Government services may also include value added from public investment projects. However, the data is not detailed enough to distinguish market from non-market in these sectors.

5
**<u>Table 5.  Interactions of Business-As-Usual Survey Approach (T1/IHS4) with Individual and Household Attributes</u>**

||||**Men**|||||**Women**|||
|---|---|---|---|---|---|---|---|---|---|---|
||**Repor**|**ted**|**Econ**|**omic**|**SDG**|**Report**|**ed**|**Econom**|**ic**|**SDG**|
||||||**Owner**|||||**Owner**|
||**Exclusive**<br>**(1)**|**Joint**<br>**(2)**|**Exclusive**<br>**(3)**|**Joint**<br>**(4)**|**(5)**|**Exclusive**<br>**(6)**|**Joint**<br> <br>**(7)**|**Exclusive**<br>**(8)**|**Joint**<br>**(9)**|**(10)**|
|T1/IHS4|0.024|0.027|0.080*|0.085|0.018|0.017|0.001|0.026|-0.005|0.035|
||[0.46]|
Policy Research Working Paper 11079

# **Abstract**

This study examines the complex relationships between rainfall shocks, agricultural productivity, and rural economic activity in Rajasthan, India’s largest state. Using district-level agricultural data from 1990 to 2015, enterprise surveys from 2010 to 2016, and household consumption data from 2014 to 2016, the research analyzes three key relationships. First, positive rainfall shocks increase agricultural productivity by approximately 7 percent compared to negative shocks, with irrigation infrastructure significantly moderating this effect. Second, these weather-induced agricultural productivity changes have substantial spillover effects on rural non-farm enterprises, particularly those engaged in retail trade. Specifically, positive rainfall shocks in-crease enterprise revenues by 25.7 percent and value-addition by 30.3 percent, primarily through increased local demand for non-tradable goods. Third, rural household consumption responds positively to favorable rainfall conditions, with monthly per capita expenditures increasing by 6 percent during positive rainfall shocks. This increase is predominantly driven by higher spending on luxury goods rather than essential items, supporting the demand-side channel through which weather shocks affect non-farm enterprise performance. These findings highlight the strong interconnections between agricultural conditions and non-farm economic activity in rural areas, with important implications for policies aimed at building rural economic resilience in the context of increasing weather variability.

This paper is a product of the Agriculture and Food Global Department. 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 fdarko@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 should be cited accordingly. The findings, interpretations, and conclusions expressed
team greeted deportees after they had been processed and as they were leaving the airport. Enumerators were instructed to randomly select individuals to approach with information about the study and not to select based on any observable characteristics. In practice, this meant selecting every fifth deportee or so, given that so many left the airport at the same time. This methodology gives us confidence that we obtained a reasonably representative sample, as do demographic similarities regarding gender between our data and official ICE data tracked by Syracuse University’s TRAC Immigration. More precisely, 11 percent of Guatemalans deported from 2004 to 2020 were women, and 8 percent of our sample were women. However, we are not able to more thoroughly compare our sample’s demographic characteristics to official records because many other characteristics of deportees are withheld by ICE.

Respondents were offered 50 Quetzales, equivalent to about 6 _._ 50 USD, to participate in the survey. Upon survey completion, respondents were offered an additional 50 Quetzales to provide information for a follow-up survey. We interviewed 1,357 deportees upon their arrival to the country. Respondents who chose to provide contact information during the first round of the survey were contacted for a 1-month follow up as well as a 6 month follow up. The follow-up surveys were conducted over the phone, and respondents who completed these surveys received a phone balance credit of at least 50 Quetzales for each survey. Phone surveys continued through October of 2020, and we collected a total of 645 follow-up surveys across the two waves, with 210 respondents interviewed in both follow-up waves. Questions relevant to our analysis here were primarily asked in rounds 2 (1-month followup) and 3 (6-months followup). We pool round 2 and round 3 results, and all regressions utilize robust standard errors clustered by respondent. The multi-wave survey contains a wide variety of questions covering topics ranging from demographics to experiences in the United States and Guatemala; specific wording for relevant survey questions is included in the online appendix.

Additionally, we conducted 18 semi-structured interviews with
balance sheet-type data.<sup>4</sup> Table 1, Panel A reports distribution of firms in our sample by industry and size.

About 60% of the surveyed firms work in manufacturing and 30% is engaged in service activities. Access to selling markets is fairly dichotomous: 63% of the firms sell only domestically – these are mostly micro and small enterprises engaged in manufacturing and services.<sup>5</sup> Exporters sell on average more than 60% of their output to foreigners, indicating that there might be important costs to set up production for export. About 75% of the exporters sell to EU markets (to Germany, Italy, and Greece). Half of these sell also to Eastern Europe and Central Asia markets, in particular to Macedonia, Russia, and Turkey.

Foreign ownership is highly concentrated. In the sample for which TFP can be estimated, 10% of firms are foreign owned and, among these, 75% of firm capital is in foreign hands.

Firms report, amongst others, the value of total sales and fixed assets as well as information on employees, wages and costs as a percentage of total sales. We use this information to obtain estimates of TFP.

The survey has several different indicators of access to credit. Firms report whether they have a credit line or an overdraft facility. As our main indicator of access to credit, we use a variable (LINE) taking value of one if the firm has either overdraft or a credit line and zero otherwise. We combine overdrafts and credit lines together as

> 4 See “Investment Climate and Regulatory Cost Survey,” IFC, for more details on the survey. 5 Firm size is defined as follows: micro enterprises (up to 10 employees); small (between 11 and 50 employees); medium (between 51 and 100 employees); large (more than 100 employees).

6
|0.844|0.825|0.809|0.854|_0.262_|_0.454_|_0.715_|_0.869_|
|Head of household can read and write (0/1)|0.751|0.722|0.781|0.832|0.820|0.854|_0.433_|_0.752_|_0.145_|_0.441_|
|Raven's index (0/3)|0.917|0.887|0.948|1.06|1.09|1.000|_0.622_|_0.693_|_0.180_|_0.795_|
|Related to government officials or influentials (0/1)|0.155|0.175|0.135|0.146|0.124|0.188|_0.485_|_0.440_|_0.397_|_0.468_|
|Socializes with government officials or influentials (0/1)|0.155|0.175|0.135|0.146|0.124|0.188|_0.485_|_0.440_|_0.397_|_0.468_|
|House has concrete floor (0/1)|0.539|0.526|0.552|0.504|0.494|0.521|_0.741_|_0.774_|_0.729_|_0.776_|
|Food insecurity PCA index|-0.291|-0.115|-0.468|-0.298|-0.322|-0.254|_0.215_|_0.875_|_0.493_|_0.560_|
|Has cultivable land larger than 1 Ha (0/1)|0.389|0.392|0.385|0.445|0.427|0.479
With regard to the relationship between computer-related skills and earnings premiums, the results are more heterogeneous; there is as yet no consensus on whether this relationship is driven by an increase in computer-specific human capital or changes in the organization of the workplace.

# **III. Data**

This paper uses the STEP Skill Measurement surveys from eight low- and middle-income countries: Armenia, Bolivia, Colombia, Georgia, Ghana, Kenya, Ukraine, and Vietnam. It gathers information from urban adults between the ages of 15 and 64 and includes three unique modules that cover various measures cognitive and noncognitive skills.

The STEP surveys provide a direct, objective assessment of _reading proficiency skills_ , which is scored on the same scale as the OECD’s PIAAC assessment. The assessment includes three parts that together provide a measure of reading proficiency among adults in each of the countries surveyed. The items used in STEP were developed based on the literacy frameworks developed for PIAAC, which defines literacy as: _“understanding, evaluating, using and engaging with written texts to participate in society, to achieve one’s goals, and to develop one’s knowledge and potential”_ (OECD, 2012). This definition provides a broad understanding of the processes and goals of literacy as measured in STEP. The main aspects of the construct—contexts for reading and underlying cognitive processes required to complete the presented tasks—have been taken into consideration when selecting the texts and developing items included in the STEP literacy assessment (Pierre et al., 2014; Educational Testing Service, 2014). The scores of the assessment range from 0 to 500 and represent six levels of proficiency.<sup>8</sup> In addition to reading proficiency, several items on the STEP survey capture data on _computer use at work_ , which we use as a second measure of cognitive skills for this study. This variable provides the frequency and complexity of computer use on the job and was selected to help determine the extent to which these skills are
# <mark>3.1.3 Method of Analysis</mark>

The analysis undertaken in this study involves two steps. First, the magnitude and different sources of bias introduced in the phone survey selection and interview process are identified. Several subsamples are compared, reflecting the eligibility, selection, and interview process for the HFPS in the four countries. To measure the bias, pairwise comparisons of weighted means across a wide variety of household characteristics is carried out. In order to assess the extent of **coverage bias** , differences between the full F2F survey sample and the _eligible_ sample for the HFPS (i.e. households with contact information) are examined. To measure **sample representativeness** in Nigeria, the profile of the selected sample is compared with the frame of eligible households. Lastly, to estimate **nonresponse bias** , the sample of households successfully contacted and those successfully interviewed is compared with the overall HFPS sample. Comparing the profile of characteristics for these samples will provide a more refined impression of the bias introduced throughout the course of the phone survey process. This comparative analysis will also reveal at what stage in the selection process the bias is the most substantial.

After conducting the comprehensive assessment of bias, an assessment of the reweighting adjustments to counteract bias is conducted to see how effective these methods were at reducing bias. Weighted estimates for the diverse set of characteristics examined in the first analysis is presented for the full representative F2F survey as well as the HFPS. The F2F survey characteristics serve as the benchmark and are compared with the profile of characteristics obtained from the HFPS sample applying the weights that include the bias adjustments (as described in Section 3.1.3). Comparing these two sets of weighted characteristics will show how much bias remains in the sample after the correction. However, the relative effectiveness of the bias adjustments is further analyzed by computing a second set of HFPS weights which _exclude the bias adjustments_ . The process of calculating these “unadjusted
insecurity after the earthquake was more connected to pre-earthquake household wealth than to asset losses experienced by households after the quake.<sup>8</sup> Hence, it appears that households were able to partly buffer the impact of the shock. Nevertheless, it was not possible with our setting to isolate the impact of food assistance

> 2 _Cf._ Echevin (2010).

> 3 _Cf._ CNSA (2010a).

> 4 More precisely, the questionnaire collected information on mortality, displacements and housing damages, income sources and durable goods before and after the earthquake as well as food consumption and other expenses, agricultural activities, survival strategies and the nutritional status of children.

> 5 _Cf._ CNSA (2010b).

> 6 Based on a random survey in Port-au-Prince, Kolbe et al. (2010) have shown that 18.6% of all households were experiencing _severe_ food insecurity six weeks after the earthquake. They also estimated that 24.4% of the respondents’ homes had been completely destroyed by the quake.

> 7 People were _de facto_ poorer and more food insecure in camps according to February 2010 survey.

> 8 Household wealth is proxied by an asset index, obtained from a multiple component analysis using housing characteristics and household durable goods.

2
|
||[0.056]**|[0.093]|[0.103]|[0.101]|
|Obs|21,411|21,411|3,222|3,222|
|R2|0.181|0.109|0.257|0.231|
|_B. By social perceptions about women_|||||
|<br>Female in less traditional countries|0.045|0.033|0.012|0.029|
||[0.093]|[0.115]|[0.110]|[0.099]|
|Female in more traditional countries|0.23|0.102|0.485|0.423|
||[0.070]***|[0.162]|[0.242]**|[0.253]*|
|Obs|21,411|21,411|3,222|3,222|
|R2|0.181|0.109|0.26|0.235|

Sources: World Bank Enterprise Surveys and World Value Surveys. Notes: The sample includes 61 countries, of which 28 are classified as more traditional and 33 as less-traditional. All models control for manager experience, indicators of firm age, legal status, size, whether the firm exports, whether it has financial statements certified by external auditors, the percentage of the firm that is privately owned, and industry, country, and year fixed effects. Standard errors are clustered at the country level. *** significant at 1%, ** at 5%, * at 10%.

The finding that female-managed firms receive loans of lower value compared to similar malemanaged firms despite being more profitable on average may partly explain the higher _arpk_ in firms managed by women. If this were indeed the case, then capital misallocation would appear stronger in
_Source_ : World Bank staff calculations based on utility data.

In the medium to long term, there are further opportunities to reduce the cost of service. While a quick and practical solution in many contexts, HFO-based generation still represents a relatively expensive source of electricity, renders countries vulnerable to international oil price shocks, and has relatively high negative environmental externalities. Where alternative domestic sources of energy are not available, power trade can open opportunities for accessing lower-cost, clean and reliable power. For example, the OMVG interconnection ( _Organisation pour la Mise en Valeur du fleuve Gambie,_ The Gambia River Basin Organization) in West Africa will allow Senegal, The Gambia and Guinea Bissau to access power imports from hydropower in Guinea at a fraction of the cost of HFO- and diesel-based generation, which dominates the existing power mix in those countries. Likewise São Tomé and Príncipe is preparing to rehabilitate a dilapidated hydro plant.

> 8 For the purposes of this simplified analysis, it is assumed that 5 percent of the diesel consumed would still be used, for example, in the process of warming up engines from sitting idle. Heat rates of 9.81 and 11.13 gigajoules per megawatt-hour are assumed for HFO and diesel, respectively. Fuel prices in the reference year are used (Table 12).

52
|2.3|2.3|3.5|2.5|2.7|

_Source:_ Authors’ calculations.

# **Mexico (ENIGH 2008)**

The data are taken from the 2008 National Household Income and Expenditure Survey (ENIGH) conducted by the National Institute of Statistics and Geography (INEGI) in Mexico. The fieldwork for the survey was carried out between August and November 2008.

The value of all non-purchased items was about 30 percent of total purchased expenditure, while non-purchased food accounted for about 62 percent of all non-purchased items. These ratios were approximately constant across the quintile groups. Expenditures were not deflated because adjustment factors were not available.
# 7.4) The Emergence of Today's Homo Economicus

Finally, in Paul Krugman's words<sup>22</sup> , "The theory has become more exciting, more dynamic and much closer to the world view long held by insightful observers who were skeptical of the old conventional wisdom." A backward look at our discipline provides perspective on why development economics has changed so much over half a century.

A Homo Sapiens, the author of these lines is the product of four million years of natural selection. Homo Economicus has evolved at a far more dizzying speed. The Macroeconomicus and Microeconomicus varieties were so different after the war that many thought them to be distinct subspecies. Many differences remain in spite of limited interbreeding. This rapid evolution will surely continue, as the paradigm that guides our work reflects economists' efforts to understand the real world.

Keynes' consumer was a simple beast, not so different from a worm inching its way on a sandy sea bottom, gulping sand into one end of which it spews out a lesser quantity at the other, the 23 difference being the organic matter that it digests . The discussion of investment in the General Theory reflects a subtle Cambridge understanding of capital theory but this leads to little and what readers retained was that investors are driven by animal spirits. John Bull could stand many things but not a 2 percent interest rate, thus the liquidity preference schedule did not intersect the X axis.

In standard microeconomic theory, consumers were alone in a world which transmitted price signals. So little was deduced from the assumption of utility maximization24 that many professors "started from demand". The theory of monopolistic competition examined how businessmen matched marginal cost and marginal revenue, concepts that no one has found a way to quantify from accounting and market data.

Price theory was so far removed from the real world that many came to accept that prices did not matter, a conviction that was buffered by surveys by Oxford Keynesians that purported to show that interest rates does not
1 million individuals.<sup>24</sup> The bulk of the forced displacement of people took place in the five IS‐affected governorates, with Anbar, Salahadin and Nineveh alone accounting for 90 percent of the displaced families (Figure 6). These internally displaced persons (IDPs) have sought refuge across Iraq – 63 percent of IDPs have crossed into other governorates, about half of them into the three governorates of Iraqi Kurdistan.

As expected, the welfare levels of this group –i.e. consumption per capita – has shrunk by more than double that for the population on average. Household consumption per capita would have decreased by almost 22% between scenarios. The impacts on total income per capita would have been more severe (i.e. ‐61.6%) under the assumption of smoothing consumption over difficult times. These were mainly driven by a massive reduction in labor income (i.e. ‐62.5%) as a consequence of job loss. Unemployment rate rises up to 27% among this population which is almost 3 times higher than the increase suffered by the whole population.

> 23A higher concentration of population in the center of the welfare/consumption distribution produces narrow consumption intervals for each decile. The narrower the decile consumption interval, the higher the likelihood of household to jump into a different decile position. Given the small positive impacts of non‐labor income mentioned above, very few households in these deciles suffered income gains as a consequence of the crises that are large enough to push them to a higher decile. However, these movements are negligible relative to the other options.

> 24Source: IOM‐OIM DTM Data January to December 25, 2014.

20
relative to shorter recall windows.<sup>4</sup> The evidence on recall windows as it applies to labor activities, however, is more mixed. In a study based in Tanzania, Arthi et al. (2018) compare reported contributions of farm labor in an agricultural plot-based module using weekly recall with those from an end of season recall window. Longer recall windows exaggerate the number of hours worked per person by a factor of four, although the reported number of active plots and individual level participation are undercounted. In our rural sample in nearby Malawi, we find reductions in reported labor contributions using the longer recall periods relative to a shorter recall window, but no overall difference in hours worked, the intensive margin on which Arthi et al. (2018) find positive effects. In urban labor markets, Heath et al. (2021) examine very short recall windows and find modest effects of switching from weekly to daily recall with higher reported self- employment spells but no impact on wage employment. However, Garlick et al. (2020) find that weekly versus monthly surveys did not influence data quality or reported microenterprise activities.

This paper also links to a second area of the methods literature centered on the use of proxy responses for data collection. Of note, Bardasi et al. (2011) find that males are more affected by proxy losses in reported agricultural labor activities than women, though this is reduced when the primary respondent is his wife or well-educated. By contrast, Serneels, Beegle, and Dillon (2017) find that proxying does not affect estimates of returns to education. Another related paper in this literature is by Kilic et al. (2022), that also intersects with the recall literature on labor measurement. They use two nationally representative surveys in Malawi conducted in the same year but following different research protocols. They find underreporting of certain labor activities in the survey using “business as usual,” that allowed for proxy reporting and presence of other household members, relative to