rafmacalaba/datause-encoder-data huggingface dataset:
at first job, less risky sexual activity, older age at first parenthood, and participation in activities. Males with a good relationship with their fathers or mothers stay in school, are not inactive, and participate in activities. Girls’ relationships with their fathers is more related to staying in school, not working and greater participation in activities while the relationship with the mother is also related to safe sexual practices. Although living with both parents is important for all seven behaviors, the actual relationship with parents is also important, as shown by controlling for the former. This relationship is largely an emotional connection, since engaging in activities with parents did not emerge as a strong protective factor in the analysis.

Abuse in the family weakly emerges as a deterrent to positive behaviors. Physical abuse in the household explains the variance of early working and early and unsafe sexual behavior for females but it does not emerge as a potential explanatory variable for male behaviors. Parental responsiveness to youth behaviors, whether good or bad, is a good explanatory variable for both males and females. Poor parental response to misbehavior – which may range from a lack of parental responsiveness (no connectedness) to verbal abuse to physical abuse – is negatively correlated with an older age at first job, safe sexual behavior, later age at first parenthood and a healthy attitude towards alcohol for both genders in Mexico. Poor parental response to good behavior is negatively correlated with school completion, an older age at first job and participation in activities for both genders. The small role played by household abuse may be surprising given how it is negatively correlated with all behaviors in Tables 3a and 3b and that it emerges as a key factor in the Caribbean (World Bank 2003) and Brazil (World Bank 2007) research. Three factors may be at play. First, the conditional analysis controls for household poverty, which is strongly correlated with all behaviors and with household abuse; the other studies and Tables 3a and 3b were unconditional estimates. Second, the incidence of household abuse is small, so there may not be sufficient variation to explain the variance in the dependent variable. Third, the relationship variables may be picking up the variance in the effect of parental abuse. Given these explanations, the fact that family abuse emerges as an important factor for girls demonstrates how damaging household abuse is for young women’s behavioral choices.

16
average FOREIGN OWNERSHIP as our non-ECA sample, there is still a significant difference in the response of PRIVATE CREDIT to FOREIGN FUNDING shocks. Therefore, we conclude that foreign ownership does not appear to be the factor that is driving the difference of between the (full) ECA and non-ECA samples.

To summarize our findings, we show that removing from the full ECA sample countries with very high FOREIGN FUNDING or very high LDR makes the “truncated ECA” sample similar to the rest of the world in terms of the response of PRIVATE CREDIT to FOREIGN FUNDING shocks. This suggests that high FOREIGN FUNDING and high LDR are indeed factors that are driving the observed differences between the (full) ECA and non-ECA samples. In contrast, high FOREIGN OWNERSHIP is not driving these differences because even when high FOREIGN OWNERSHIP countries are removed from the ECA sample and the truncated ECA sample has lower average FOREIGN OWNERSHIP than the non-ECA sample, there is still a significant difference in the response of PRIVATE CREDIT to FOREIGN FUNDING shocks. These results provide more direct evidence that high FOREIGN FUNDING and high LDR ratios were key factors in explaining the higher sensitivity of PRIVATE CREDIT to FOREIGN FUNDING shocks in ECA, while high FOREIGN OWNERSHIP per se did not account for this.

# **VI. Summary of Conclusions and Policy Implications**

By applying PVARs to a global country panel database we show that bank credit growth to the private sector is highly sensitive to cross-border funding shocks around the world. We find that this relationship is significantly stronger in the average ECA country where the response is 72% larger compared to the average country in the rest of the world. At the same time, we show that foreign ownership _per se_ does not explain the different credit responses in our sample of countries. Instead, our results indicate stronger responses in countries with high loan-to-deposit ratios and stronger reliance on foreign funding. Higher loan-to-deposit ratios make banks more

> differences between responses of private credit to foreign liabilities between this very small sample and the nonECA sample.

28
The last section summarizes the paper’s main conclusions and the implications of our results for future research. Appendix A defines the variables used in the paper. Appendix B provides statistics on the survey design, data quality checks, balance, and survey compliance. Appendix C elaborates on the aggregation of triweekly interviews to weekly labor reports. Appendix D presents additional tests.

# **2. Recall Bias, Telescoping, and Interview Mode in Labor Surveys**

A substantial body of literature (summarized in Beckett et al. 2001 and Bound et al. 2001) shows that retrospective reports are prone to recall bias , the magnitude of which depends on factors such as the salience of the events to be recalled, social desirability, respondent characteristics (Bardasi et al. 2011), and the reference period (Arthi et al., 2018, de Nicola and Gine, 2014).<sup>4</sup> Longer reference periods have been associated with increased recall bias that leads to differences in reported labor outcomes (see e.g. Horvath, 1982, Mathiowetz and Duncan 1988, and Pierret, 2001). Studies that use time diaries, in which the reference period is typically very short, yield lower estimates of labor supply (Barret and Hammermesh, 2016; Duncan and Stafford 1980; Hamermesh 1990; Robinson and Bostrom 1994; Bonke 2005; Robinson et al. 2011; Juster and Stafford, 1991).

The length of the reference period can also impact telescoping error, the <mark>tendency of respondents to r</mark> eport events as occurring earlier (backward telescoping) or more recently (forward telescoping) than they actually did (Neter and Waksberg, 1964; Mathiowetz, 1986; Mathiowetz and Duncan, 1988; Sudman and Bradburn, 1974, 1982). While telescoping bias can go in either direction, it usually results in overreporting when the reference period is short (Bound et al., 2001), 4 The choice of reference period in labor market surveys has been the subject of extensive debate (Hussmans, Mehran, and Verma 1990; Stewart 2014). The International Labour Organization (ILO) identifies both a day and a week as appropriate reference periods, as they correspond closely to an instantaneous (stock) measure of employment and are less vulnerable to the memory-dependent errors that arise over longer periods of recall. Most labor market surveys use a reference period of one week, because of both the practicality of measurement and consistency with other sources. When full-time formal-sector employment is the norm, using weekly as opposed to daily recall has the additional advantage of resulting in a lower variance while giving similar average results. The ILO notes that when intermittent, casual, and short-term employment is widespread, as is the case in developing countries, shorter reference periods may enhance accuracy. If self-employment is more volatile than wage employment, one would expect the choice of the reference period to have a greater impact on reporting of self-employment than wage-employment.

5
WPS3986

# **REFORMING THE INVESTMENT CLIMATE:**

# **LESSONS FOR PRACTITIONERS**

**Sunita Kikeri**

**Thomas Kenyon Vincent Palmade**

### World Bank Policy Research Working Paper 3986, August 2006

_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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

## **Investment Climate Department**

**Private Sector Development Vice-Presidency World Bank/IFC**
Given the mixture of different crops grown in the survey areas, we use the generalized bounds of 8° Celsius and 32° Celsius (for example, Schlenker and Roberts, 2008). In our specific case, any daily minimum or maximum temperature below 8° Celsius is treated as being 8° Celsius and any daily minimum or maximum temperature above 32° Celsius is treated as being 32° Celsius. Thus a day with a minimum and maximum temperature of 8° Celsius or below will yield no GDDs, whereas a day with a maximum and a minimum temperature of 32° Celsius or above will yield 24 GDDs.

For our measures of weather shocks we first calculate the municipal historic mean rainfall and GDD between 1951 and 1985 for the agricultural year, for the wet season and for the pre- _canícula_ period. Given that there is incomplete information for some months for some of the municipalities (i.e. none of the 20 closest weather stations reported data for 5 or more consecutive days), in our sample of rural municipalities, the average climate is based on 15 to 35 years of information. 75% of the rural households in our samples live in municipalities with at least 30 years of complete weather information from 1951 to 1985.<sup>18</sup> Our chosen measures of weather shocks, , are based on the degree of deviation from the 1951-1985 average weather. A shock is defined by an indicator variable identifying those observations where the weather variable is more than one standard deviation from its long-run mean. A municipality is defined to have experienced a negative rainfall shock if the prior period‘s rainfall was at least one standard deviation less than the average 1951-1985 rainfall; and a municipality is defined to have experienced a positive rainfall shock if the prior period‘s rainfall was at least one standard deviation more than the average 1951-1985 rainfall. Thus, there are in total four measures describing the prior year‘s (or wet season‘s or pre- _canícula_ period‘s) weather. Table 2 shows the 1951 to 1985 average weather conditions by regions for Mexico. One standard deviation rainfall shock translates to an average of about 30% difference in annual or wet season rainfall and a 50% difference for the pre- _canícula_ period. The GDD shocks are, on average, about 8% deviations from the mean. The climate in each of the regions is distinct and even within a region there is much variability. In general, however, the North is drier than the rest of the country and the Center is colder than the rest of the country.

> 18 To balance the need to calculate the historic means with as many years of information as possible but excluding recent years which may have been affected by changing climate, we construct the historic means and standard deviations of the weather variables using data from 1951 to 1985.

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30

# **Figure 7 Pipeline Capacity Booking and Trading**

<!-- Start of picture text --> Shipper 1 .4 (- Shipper 2<br>[<br>1 1<br>British Gas TransCo<br>entry point entry point --- -----<br>capacity capacity<br>NTS NTS<br>___ ___ exit point exit point ____-__-d<br>capacity capacity<br>LDZ LDZ<br>l... _ exit point exit point ]------- J<br>capacity capacity J<br>Customer site Customer site<br>]<br>Physical connection - - - Financial flow -4 0 Information flow<br><!-- End of picture text -->

- @ Shippers book capacity from British Gas TransCo on all three levels (typically a 12-month contract). Shippers trade free capacity and notify British Gas TransCo of the new capacity owner. Shippers settle the trade financially.

Note: NTS is national transmission system; LDZ is local distribution zone.

Source: Author's compilation

# **Primary capacity market**

In the U.K. primary capacity market shippers typically book capacity under a 12-month contract with BGT at three locations:

-

- * At an entry point to the national transmission system (NTS) NTS entry capacity.

-

- * At an exit point from the national transmission system NTS exit capacity.

-

- * At an exit point from the local distribution zone (LDZ) LDZ capacity.

In addition, shippers can book storage capacity, consisting of storage space and deliverability (a rate of gas withdrawal from storage).
16 percent between 2003 and 2013 while the share of vulnerable and middle class households increased by 5.7 percent and 9.8 percent respectively. Notably, the South South region shows the largest decrease of households in the poor group (21.3 percent) and the highest increase in the middle class group (17.4 percent).

# **V. Conclusions**

Why is it so important to define and quantify the middle class in Nigeria and in general in developing countries? Because, we argue, the middle class is associated with the idea that talent and effort qualities produce social mobility and that, in general, middle class is an agent of change from an economic, social, and political perspective. It follows that, looking at the size and characteristics of middle class tells us a lot about the structural transformations a country is undergoing.

Aware of the growing importance middle class studies are gaining in developing countries, our paper purports to quantify the Nigerian middle class size in a rigorous way. The vulnerability approach to middle class (VAMC) (Lopez-Calva and Ortiz-Juarez, 2011) is the method we employ to identify an income threshold above which a household can be classified as middle class. According to this method, in developing countries the middle class group can be defined residually from the vulnerability analysis: those for which the probability of falling into poverty is below a certain threshold (10%) can be considered part of the middle class.

Four findings are noteworthy. First, the percentage of Nigerians above the estimated threshold (3 dollars per capita per day) is roughly 20 percent. This 20 percent coincides with Standard Bank estimates when summing lower middle class and middle class (Standard Bank, 2014). If he threshold used for Latin America of around 10 dollars is used, the share of Nigerians qualifying for middle class status will be more than halved.

Second, the geographical distribution of those belonging to middle class mirrors that of the poor (NER, 2014). Most of the middle class is concentrated in the South West where about 30 percent of the population is living above the threshold while in the rest of the country the share reduces to 25 percent or less. In the poorest regions in the North less than 10 percent of the population qualifies as middle class.

Third, the middle class group profile is the expected and the estimated threshold seems to divide groups (middle class and vulnerable) with significantly different characteristics. Higher education, better employment opportunities, possession of relevant assets, and residence in 21
21 since it owns a significant stake in more than half of its companies and a controlling<sup>stake</sup> in 9% of its companies. This situates Sporitelna ahead of the two<sup>foreign bank sponsored</sup> funds - Creditanstalt and Zivnostenska Banka. In fact, Zivnostenska Banka does not have<sup>a</sup> controlling stake in a single company. In general, however, in the set of top<sup>ten funds, the</sup> non-bank funds opted most often for concentrated portfolios,<sup>a precondition for any</sup> corporate governance action.

For the most part, IPFs have kept the portfolio they acquired through<sup>the five bidding</sup> rounds with no major changes in the portfolio, at least in the funds analyzed<sup>here27.In the</sup> fund interviews most of them reported that the predominant activity between end-<sup>1992 and</sup> mid-1994 can be seen as portfolio clearing. This means that most funds<sup>sold shareholdings</sup> of enterprises in which they held only a small stake, because there was<sup>a strategic investor</sup> or because the share price seemed to be 'unusually high'. Table 13 analyzes portfolio clearing by looking at the decrease or increase in number of companies in the portfolios. Most funds across all three fund categories tried to focus their activity on a smaller number of companies by decreasing the number of portfolio companies. Again, some non-bank funds (Harvard and PPF) and the foreign bank sponsored fund from Creditanstalt showed the greatest interest in further reducing the number of companies in the portfolio.

**Table 13: Rank of IPFs by change in number of companies in**<sup>**portfolio between**</sup> **December 31, 1992 and June 30, 1994** (in %)

|| CA|AB|KB|PPF|CP|CS|YSE|HCC|ZB|lB|
|---|---|---|---|---|---|---|---|---|---|
|-23|-16|-8|-8|-8|-7|-5|-2|9|20|

Remark: for fund names and fund classification see Table 3. Source: Fund interviews.

Since owners can be represented in companies in which they own less<sup>than</sup> 10%<sup>of a firm's</sup> capital, a more precise indicator of the relationship between owners and<sup>company would be</sup> the number of companies in which the fund is represented on the board<sup>in relation to the</sup>

**27** One of the reasons for this is the low liquidity of the market; see Jaros and Sanders<sup>(1994, 9).</sup>
- Brambilla, I., Lederman, D., & Porto, G. (2012). Exports, export destinations, and skills. _American Economic Review_ , _102_ (7), 3406–38.

- Branstetter, L. G., Kovak, B. K., Mauro, J., & Venancio, A. (2019). _The China shock and employment in portuguese firms_ (Working Paper No. 26252). National Bureau of Economic Research.

- Brugu ́es, F., Brugu ́es, J., & Giambra, S. (2022). Political connections and misallocation of procurement contracts: evidence from Ecuador. _Strutural Transformation and Economic Growth Working paper STEG WP012_ .

- Caballero, R., & Hammour, M. (1994). _The cleansing effect of recessions_ (Vol. 84) (No. 5).

- Carneiro, A., Guimar ̃aes, P., & Portugal, P. (2012). Real wages and the business cycle: Accounting for worker, firm, and job title heterogeneity. _American Economic Journal: Macroeconomics_ , _4_ (2), 133–52.

- Colonnelli, E., & Prem, M. (2022). Corruption and firms. _The Review of Economic Studies_ , _89_ (2), 695–732.

- Colonnelli, E., Prem, M., & Teso, E. (2020). Patronage and selection in public sector organizations. _American Economic Review_ , _110_ (10), 3071–99.

- Cusolito, A., & Maloney, W. (2018). _Productivity revisited: Shifting paradigms in analysis and policy_ . World Bank Publications.

- Dauth, W., Findeisen, S., & Suedekum, J. (2017). Trade and manufacturing jobs in Germany. _American Economic Review_ , _107_ (5), 337–42.

- Dauth, W., Findeisen, S., & Suedekum, J. (2021). Adjusting to globalization in Germany. _Journal of Labor Economics_ , _39_ (1), 263–302.

- Davis, S. J., & von Wachter, T. M. (2011). _Recessions and the cost of job loss_ (Working Paper No. 17638). National Bureau of Economic Research.

- Dias, D. A., & Robalo Marques, C. (2021). Every cloud has a silver lining: Cleansing effects of the Portuguese financial crisis. _Oxford Bulletin of Economics and Statistics_ , _83_ (2), 352–376.

- Di Giovanni, J., Levchenko, A. A., & Mejean, I. (2018). The micro origins of international business-cycle comovement. _American Economic Review_ , _108_ (1), 82–108.

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Combining psychometric variables with machine learning has also been shown to be predictive of returns to larger loans (Bryan et al., 2021). This finding potentially indicates a use case for psychometrics in targeting larger loans in donor-subsidized lending, or incorporating psychometrics into equity products where the MFI objective function includes returns rather than just repayment. More research is needed on further financial innovations to serve women and other disadvantaged groups who lack assets to secure growth-size loans.

# **References**

- Agier and Szafarz (2013). Microfinance and gender: Is there a glass ceiling on loan size? _World Development_ , 42(6):165–181.

- Alibhai, S., Buehren, N., Coleman, R., Goldstein, M., and Strobbe, F. (2018). Disruptive finance : Using psychometrics to overcome collateral constraints in Ethiopia. _World Bank Working Paper Series_ , 30(1):S67–S76.

- Arr ́aiz, I., Bruhn, M., Roth, B. N., Ruiz-Ortega, C., and Stucchi, R. (2021). Borrower leakage from costly screening: Evidence from SME lending in Peru. _Journal of Development Economics_ , 153:102719.

- Arr ́aiz, Bruhn, and Stucchi (2017). Psychometrics as a tool to improve credit information. _The World Bank Economic Review_ , 30(1):S67–S76.

- Benjamini, Y. and Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. _Journal of the Royal statistical society: series B (Methodological)_ , 57(1):289–300.

- Berge, L. I. O., Bjorvatn, K., and Tungodden, B. (2015). Human and financial capital for microenterprise development: Evidence from a field and lab experiment. _Management Science_ , 61(4):707–722.

25
To evaluate potential problems associated with controversial poverty headcount ratios, we present an alternative scenario using Deaton’s (2003) regional poverty estimates for Haryana. This gives a much lower BPL threshold of 17% and 11% for the rural and urban sectors respectively in 1993, and 6% and 5% in the subsequent rounds based on estimates for 1999. Our results are not substantively changed (Tables 8 and 9 show the re-estimated regressions), which suggests that program effects may be driven by changes occurring at the lower end of the wealth distribution.

# **5.2 Community Norms**

We are concerned about the potential effects of local community norms on women’s preferences and realized sex ratios. As a result we re-estimate the regressions and include a measure of community gender preference: the sex ratio among all living children for women of the respondent’s village or primary sampling unit. This measure is significant and positively correlated with the sex ratio of the individual’s children, as expected. Notwithstanding this result, our program effect remains unaffected by its inclusion (Table 10).

# **5.3 Potential Unverified Discrepancy in Eligibility Criteria for OBC**

As earlier described, the MODE 2000 evaluation report suggested a possible discrepancy in the eligibility criteria for OBC children. Although we searched official sources and other secondary reports, we were not able to independently verify this potential discrepancy. Nonetheless, we test whether our results are sensitive to this change.

Returning to our samples, we find that the children’s analysis is likely to be unaffected by an eligibility discrepancy based on the earlier birth date. Only five children meet the alternative criteria (between 0-36 months, OBC, above the poverty line, below the income-tax criteria, and with the appropriate number of siblings, born between October 1994 and January 1996).

For women, however, a birth date discrepancy is potentially significant. About 250 OBC women in our sample meet the other eligibility criteria (above the main poverty line, below the income-tax criteria and have two children as of October 1994). Depending on their subsequent fertility, they may or may not have qualified under the new criteria. To examine this possibility, we re-estimate the analysis for women, and drop these cases. We find no substantive change in our results (Table 11).

# **5.4  Counterfactual for Child Health Investments: Prenatal or Birth Attendance**

Birthplace and prenatal care for girls versus boys provides us with an interesting counterfactual—as we would expect to find no gender-effects. Due to the conditional nature of the program’s payment and the likelihood of household credit-constraints, we 15