rafmacalaba/data-use-mentions-extended huggingface dataset:
adjusted and they have the following annual rates based on insured deposits for different risk ratings; A: 0.45%, B: 0.60%, C: 0.95%, D: 1.25%, E: 1.45%. The coverage limit in 1991 was S 2500 which has been updated according to the wholesale price index on a quarterly basis. In December 1998 it was raised to S 62,000 and just a month earlier it was only at S 13,836. The limit was S 68,474 by the end of 2003. The coverage is calculated per depositor.

_Sources_ : Own survey of deposit insurers, IADI Survey: Peru (2003), Garcia (1999), Kyei (1995).

**Philippines.** ( _Philippine Deposit Insurance Corporation-PDIC, Republic Act 3591/7800_ ) The scheme of Philippines was established in 1963. It is government legislated and administered and jointly funded. The government provided the initial capital. The central bank has made loans and borne losses. The government and the central bank are represented on the board. All deposit-taking institutions and corporations authorized to perform banking functions in the Philippines are covered and are obliged to be members of the Fund. The coverage is extended to savings and checking accounts; foreign currency, inter-bank and time deposits on a per depositor per institution basis. The coverage limits in Philippine pesos took the following values historically: 10,000 in 1963, 15,000 in 1978, 40,000 in 1984 and 100,000 since 1992. _Sources_ : Own survey of deposit insurers, Garcia (1999), IADI Survey: Philippines (2003), Kyei (1995), Talley and Mas (1990).

**Poland.** ( _Banking Guarantee Fund, Law on Banking Guarantee Fund, 1994_ ) The Polish deposit guarantee scheme was established in 1995. It is officially administered and jointly funded. The Bank of Poland and the government contributed the initial capital. It excludes the deposits
review.<sup>11</sup> Loan officers play another important role at the enforcement stage for group liability loans. Depending on the terms of repayment, the loan officer contacts the head of the group and reminds him/her of the due dates of installments. They then typically meet again at the office in the village at some point, and in the case of overdue installment payments, the officer visits the client and negotiates repayment. During the negotiation, the loan officer also visits other members in the group and explains the likely impacts on them for non-repayment. Loan officers rely heavily on their social skills, experience, and prior knowledge of the clients and businesses in performing these tasks. In case of any delay or failure in negotiation, the loan officer is required to report it to the credit committee.

CFPA microfinance also introduced modest financial incentives to its loan officers, who were rewarded for high lending volumes and low shares of delinquent loans. Loan officers receive a flat base wage and a bonus for originating loans that perform well. Delayed installment payments therefore negatively affect their bonuses. The compensation scheme was designed to encourage loan officers to expand outreach, while avoiding loans to riskier clients that would become non-performing.

# 3. Data Sources and Variable Construction

We rely on data from three sources to undertake our analysis. We first use data on the inventory of loan disbursements and overdue repayments from 2006 to 2010. CFPA microfinance has developed a central database that documents the details of every loan disbursement undertaken at all the county branches, including disbursement date, loan size, interest rate, maturity, loan scheme (group guarantee or individual liability lending), purpose of the loan, and the corresponding loan officer. This information is maintained in CFPA’s SQL server from which the inventory of loan disbursements were directly exported. For overdue repayments, scheduled and actual dates of

> 11 We acknowledge that loan officers are not the only influence on mission drift. But to the extent that they have little or no influence
# **1 Introduction**

How do trade shocks impact workers? What can be done to facilitate labor adjustment in response to trade shocks? Answering these questions requires an understanding of how trade shocks impact not only wages but also labor mobility. If workers can easily move across occupations, sectors, or regions, they would readily pursue alternative job options following a trade shock. For this reason, there is now a substantial body of research studying the drivers and implications of imperfect labor mobility in the international trade context.<sup>1</sup> Empirically, labor mobility is pro-cyclical: it tends to increase with positive shocks and decrease with negative shocks. As an illustration of this empirical pattern, Figure 1 depicts a positive correlation between labor mobility and GDP growth using data from Brazil.

Figure 1: GDP growth rate and labor mobility, 2004-2015 <!-- Start of picture text --> 300<br>200<br>100<br>0<br>-100<br>-200<br>-300<br>2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015<br><!-- End of picture text --> _Notes_ : The figure shows the ratio between the number of movers (workers who switch occupation, sector, or region) and the number of stayers. We use the same definitions of occupation, sector, and region as those adopted in the main analysis of the paper. See Section 2 for data sources and the precise definitions of each variable. Both series are in terms of deviations from the mean and multiplied by the inverse of their standard deviations for comparison.

There is a simple and intuitive explanation for this empirical regularity: the number of job options available to workers tends to increase with positive shocks and decrease with negative shocks. If we conceptualize workers’ mobility decision based on the choice of a _job_ , rather than the choice of occupations, sectors, or regions–all of which have empirically invariant
4 Based on within-commune variation, the analysis here identifies, for the first time, significant effects of media access on outcomes from the government provision of social services: villages with greater access to community radio exhibit greater functional literacy among children in public schools. We are also able to go further than has been possible in past research and probe the mechanisms through which greater radio access affects outcomes. First, we find no evidence that the mechanism is through government accountability: schools in villages with greater access to community radio exhibit no differences with respect to either these inputs (such as books and teachers) or the efficiency with which inputs are utilized (such as lower teacher absenteeism). Accountability effects should also manifest themselves in the collective action of villagers. However, villages‘ community radio access is uncorrelated with reports of PTA activity. Furthermore, household knowledge of recent changes in government education policies is no different in villages with greater radio access.

Instead, second, the evidence supports the proposition that media effects on public services operate through changes in parental behavior. The data allow us to address three questions related to parental behavior, none of which previous literature has been able to address, even at the level of correlations. First, does radio access correspond to exposure to more relevant information? The survey of radio programming indicates that community radios broadcast significantly more education programs than other commercial and national public stations. We confirm that villages with greater access to community radio are exposed to substantially larger numbers of programs on education issues. Second, does village access to community radio increase parents‘ own investments in children‘s education? It does: households living in villages with greater radio access purchase more books for their children. Third, does listening to community radio by households with greater access to community radio increase these investments? Again, it does: instrumenting for household
of sponsorship was 9.3 years, a monthly income increase of $13–17 over an average lifetime of work implies a modest financial rate of return to child sponsorship of 3.7–5.0%.

Our estimations of impacts on wealth in adulthood find significant impacts on adult dwelling quality from child sponsorship on proxies for adult wealth, where we find that sponsored children—especially males—are more likely as adults to live in better housing (homes with electricity and with roof and floor made of superior construction materials). Formerly sponsored men are more likely to live in homes with indoor plumbing. Impacts on adult consumer good ownership, however, are more modest and appear to be limited to substantially greater ownership of mobile phones among both formerly sponsored men and women. We also present (modest) evidence suggesting that sponsored children have fewer children in adulthood, along with much stronger evidence that both formerly sponsored men and women are less likely to live with their parents in adulthood.

What about child sponsorship, in particular Compassion’s approach to child sponsorship, could be responsible for these significant effects on income and wealth in adulthood? In related research using a separate sample of _currently_ sponsored children we explore the hypothesis that child sponsorship may improve adult incomes not merely through relieving _external_ constraints that improve schooling access, nutrition, and health, but through addressing _internal_ constraints related to imparting a greater level of hopefulness about the future and instilling greater aspirations for schooling and adult vocation. Using data on currently sponsored children, we find in Glewwe, Ross, and Wydick (2014) a causal link between child sponsorship and elevated educational and vocational aspirations among children in Kenya, and higher levels of happiness, self-efficacy, and hopefulness based on a quantitative analysis of children’s self-portrait drawings in Indonesia. Although it is yet impossible to definitively identify these increased aspirations as a causal channel to the positive impact from sponsorship on income and wealth we find in this study, what is clear from our three pieces of research on child
Policy Research Working Paper 11016

# **Abstract**

High aggregate levels of wildlife consumption in Central African cities may be depleting wildlife populations. This study explores the impacts of demand and supply-side interventions on wild meat consumption through two randomized control trials in restaurants in Kinshasa, Democratic Republic of the Congo: a demand-side experiment and a supply-side experiment. In the demand-side experiment, 544 subjects were given a coupon to their restaurant of choice and randomly assigned to view either a treatment video discouraging wild meat consumption or a control video unrelated to wild meat. Treatment group subjects are 31% less likely to order wild meat than control group subjects, though this difference is not statistically significant and may be affected by social desirability bias. In the supply-side experiment, the research question is whether randomly reducing the price of Moambe Chicken, a potential alternative to wild meat, affects restaurants’ total wild meat sales. The elasticity estimate indicates that a 1% reduction in the price of Moambe Chicken reduces total wild meat sales by 0.91%. Although this relationship is not statistically significant, it suggests that interventions increasing the availability and affordability of alternatives to wild meat may reduce wild meat consumption. The experiments advance previous wild meat research by utilizing actual consumption data rather than self-reported data, assessing social desirability bias, and pre-registering all statistical specifications to enhance research integrity. This paper provides preliminary evidence that both wild meat demand reduction through social marketing campaigns and supply expansion via affordable alternatives could contribute to effective wildlife conservation in Central Africa.

This paper is a product of the Development Research Group, Development Economics. 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 aenglander@worldbank.org. A verified reproducibility package for this paper is available at http:// reproducibility.worldbank.org
consistent with the results in DOP on the impact of the immigration flows of the previous decade between 1990 and 2000. More importantly, the results exhibit a certain degree of contradiction to the popular perception that immigration has large negative effects on the wages of low ~~-s~~ killed native workers in all destination countries. On the contrary, both old and young low ~~-s~~ killed workers experience wage gains and are the main beneficiaries of relatively high ~~-s~~ killed immigration in a number of destination countries, such as Australia, Canada and Switzerland.

Our model and calibration allow for differential wage effects of immigration on native workers across different age groups. This is different than the se ~~t-~~ up in DOP where there are no age group distinctions in the labor market modelling. Nevertheless, the results show that wage gains and losses are relatively symmetric across age groups within the same skill category in the vast majority of the OECD destination countries. There are some small differences for example, such as in Italy and Spain, suggesting that the (implicit) assumption of symmetric effects in DOP may not necessarily hold.

Our analysis is based on the net changes in immigrant stocks presented in Table 2. The DIOC database provides information in 2010 on the duration of stay of immigrant groups by education category. More specifically, we have data on the education composition of the migrants who arrived between 2000 and 2010. In Appendix A, we discuss in detail how we use these data to calculate the wage impact of this gross inflow, rather than the net change. In most countries, the results are almost identical (see Figure A.1) since there is high degree of correlation between the gross inflow and net change in immigrant stocks

# 4.3 Emigration

The wage effects due to emigration show different patterns when compared to those that result from changes in immigrant stocks. The low ~~-s~~ killed non ~~-~~ migrant natives now
)|
|Observations|16,857|15,389|24,891|40,468|40,468|40,468|
|R-squared|0.159|0.157|0.196|0.252|0.252|0.274|
|The mean value of the dependent<br>variables before the program|8.560|8.495|8.732|0.546|0.472|0.741|

Note: This table reports district fixed-effect RDD-DD regressions of income and poverty of households using household-level observations. Robust standard errors in parentheses. Standard errors are clustered by district and village-year levels. *** p<0.01, ** p<0.05, * p<0.1.

44
capita distribution in Sub-Saharan Africa. For instance, seven countries in the region recorded average annual per capita growth rates that exceeded 3 percent in the period 1960-2019, whereas income per capita contracted in fourteen countries during the same period. The average growth differential between these two groups of countries was about 5 percent—a margin that can produce rapid shifts in relative income per capita over time. By looking at the growth performance across subperiods, **Table 1** hints that the evolution of income per capita for the region as a whole cannot be characterized by a time trend deterministic model (either upward or downward sloping). Instead, growth per capita in the region swings from periods of fair to poor performance. Still, the great deal of heterogeneity in the evolution of GDP per capita across countries in the region signals that: (a) there is a wide dispersion of growth per capita between top and bottom performers, and (b) every country is unique in its evolution.

Inspecting the evolution of real GDP per capita for each individual country in the region, in the spirit of Pritchett (2000), reveals a diverse landscape of growth patterns in the region. Specifically, the different growth topographies exhibited by Sub-Saharan African countries can be classified into three broad groups: (a) countries with an upward-sloping trend (uphill), (b) countries with long swings (mountain ranges), and (c) stagnant countries (plains)—if not declining. **Figure 4** describes the criteria that we used to classify the growth patterns of Sub-Saharan African countries—which is derived after visually examining the trends and fluctuations of each country’s GDP per capita time series. **Table 2** lists the countries that fall into each of the three groups. Unlike industrial countries where growth is steady with occasional recessions followed by quick recoveries, long swings and stagnant periods are prevalent in the region which have contributed to the low, short-lived, and volatile growth at the regional level.
to access agricultural advice based on their own individual-specific needs.

# **3 Theory: Demand for agricultural advice under costly attention**

This section presents a stylized model that is able to explain (i) why farmers may rationally decide not to participate in extension services, and (ii) why non-agricultural shocks can increase farmers’ demand for agricultural advice and participation in extension services. The model builds upon the following three main assumptions. First, farmers have access to sources of agricultural advice (e.g., extension services), and believe that engaging with these sources has a positive effect on production. Second, requesting and benefiting from

> 11Examples of such technologies include mobile phone apps and hotlines that offer farmers the possibility to acquire information about farm practices, weather, and relevant prices, as well as online systems where farmers can send photos or show crops affected by diseases to a web camera in order to receive advice on treatment. A survey of ICT-based agricultural extension programs is provided in Aker (2011). 12The T&V system was a public extension model promoted by the World Bank from 1975 until 1995 to increase the adoption of “Green Revolution” technologies (mainly high-yielding seed varieties, fertilizer, and other agrochemicals) in more than 70 countries (Anderson, 2007).

> 13In part, this may also have been driven by the need to achieve greater scope for cost recovery in order to facilitate privatization and contracting of extension services, which are core elements of the new pluralistic model (Anderson, 2007).

8
) declined from 13 percent of expenditures in 2000 to 7 percent in 2008; undeclared purchases were most frequent in construction or renovation services (30 percent), computer software (29 percent), and tobacco products (25 percent). According to the Estonian Tax and Customs board (Eesti Maksu- ja Tolliamet, EMTA) estimates in 2007 VAT fraud amounted to 2.5 billion kroons (1.1 percent of GDP and 3 percent of state revenue); it increased to almost 4 billion kroons (1.6 percent of GDP and 4.7 percent of state revenue) in 2008;

- According to a 2008 survey by EKI, 15 percent of the employees who said that they are in favor of unrecorded salaries argued that the state has enough resources already and that unrecorded salaries are necessary for the company to survive in the current economic situation (57 percent) and/or that the tax burden is too high (56 percent);

- Underdeclaration of income is also widespread among the self-employed who represent, however, only about 10 percent of all employed persons. The selfemployed often reduce their taxable income by declaring only part of their income and by deducting personal expenditures as business expenditures from the tax base. According to estimates by EMTA, the revenue loss (social contributions and personal income tax) from undeclared income from the self-employed amounted in 2008 to 460 million kroons (0.2 percent of GDP);

- Pensioners who continue working also often evade taxes. As they are covered by health insurance they do not need to declare their salaries in order to receive health care coverage and many of them do not pay taxes.

- Kriz et al. (2007) also find that payroll and income tax evasion is most prevalent in small firms in the construction sector and in agriculture, among individuals who are

23
# **References**

**Banerjee, Abhijit** , “The Two Poverties,” _Nordic Journal of Political Economy_ , 2000, _26_ (2), 129 – 141.

- **Banerjee, Abhijit V. and Andrew F. Newman** , “Occupational Choice and the Process of Development,” _Journal of Political Economy_ , 1993, _101_ (2), 274–298.

- **and Esther Duflo** , “The Economic Lives of the Poor,” _Journal of Economic Perspectives_ , 2007, _21_

- (1), 141 – 168.

- **, , Rachel Glennerster, and Cynthia Kinnan** , “The Miracle of Microfinance,” _BREAD Working Paper 278_ , 2010.

- **Bolton, Patrick and Howard Rosenthal** , “Political Intervention in Debt Contracts,” _Journal of Political Economy_ , October 2002, _110_ (5), 1103–1134.

**Bulow, Jeremy and Kenneth Rogoff** , “A Constant Recontracting Model of Sovereign Debt,” _Journal of Political Economy_ , February 1989, _97_ (1), 155–78.

- **Burgess, Robin and Rohini Pande** , “Do Rural Banks Matter? Evidence from the Indian Social Banking Experiment,” _The American Economic Review_ , 2005, _95_ (3), 780–795.

- **, Grace Wong, and Rohini Pande** , “Banking for the Poor: Evidence From India,” _Journal of the European Economic Association_ , 2005, _3_ (2), 268–278.

**Campbell, John Y.** , “Household Finance,” _Journal of Finance_ , 08 2006, _61_ (4), 1553–1604.

- **Cole, Shawn A.** , “Fixing Market Failures or Fixing Elections? Elections, Banks and Agricultural Lending in India,” _American Economic Journal: Applied Economics_ , 2009, _1_ (1), 219–250.

- **Cole
evidence is consistent with the findings in WTO (2012) based on specific trade concerns and the results of business surveys. This finding could be consistent with two types of explanations. One possibility is that more advanced economies have substituted declining tariff

> 9 The frequency index for country _i_ is calculated as �� � ~~�~~ ∑�∑���� <u>��∙100, where �� and �� are respectively dummy</u> variables capturing the presence of one or more NTM and the presence of imports in product _j_ . Similarly, the coverage ratio for a country is calculated as �� � ~~�~~ ∑�∑����� <u>��∙100, where �� is the value of imports of product</u> _j_ . To partially offset the endogeneity problem implicit in the coverage ratio (the value of imports is lower for goods that are subject to NTMs), we use import values for three years. Beyond these simple measures, Bown (2011) presents alternative approaches to construct coverage ratios that capture both the stocks and flows of imported products covered by TTBs and calculates them for the countries covered in the TTB database. These approaches could be usefully applied to the broader set of NTMs as more data become available.

> 10 The two inventory measures are highly correlated, but the coverage ratio is generally higher than the frequency index. This shows that NTMs tend to be concentrated in highly traded products.