rafmacalaba/data-use-mentions-extended huggingface dataset:
oriented reforms. Because of the collapse of the financial sector, virtually no credit was available to the private sector. However, starting in 2001, credit to the private sector grew at progressively faster rates. For example, bank claims on the nongovernment sector rose by nearly 8 percentage points of GDP in 2003 (IMF, Article IV consultations) without any sign of deterioration in banks’ prudential indicators. Such rapid credit growth and the related widening of the current account deficit generated concerns of overheating in the economy and induced the authorities to implement restrictive measures in October 2004 to curb it.

The paper is organized as follows. Section 2 described the data. Section 3 discusses alternative TFP estimates and methodology. Section 4 presents the results of the twostage estimation and the robustness checks. Section 5 concludes.

# **2. Data description**

We use a recent survey of Bulgarian enterprises which was conducted by the IFC/World Bank in March-April 2004 (FIAS ). The survey contains information on 548 Bulgarian firms sampled according to a number of criteria: (i) size, so as to be representative of SMEs and to include a minimum of 20% of large firms; (ii) sectors, so as to mirror the distributions of Bulgarian firms across manufacturing, mining, and services; and (iii) location, so as to include firms in large cities (200), small towns (100), and the capital, Sofia. The survey reports detailed information on administrative and bureaucratic constraints to business and a limited amount of 5
23

# **USPTO Utility Patent Counts**

An alternative patent data set is that of Hall, Jaffe and Trajtenberg (2001), which covers all utility patents that were granted between January 1963 and December 1999. Utility patents are patents that are granted to persons who invent or discover any new and useful process, machine, article of manufacture, or compositions of matters, or any new useful improvement thereof. Thus this data set focuses on only one category of patents but provides data with a substantially longer time dimension. Also note that utility patents are the largest category of patents. In 1999, the number of utility patents granted reached 153,486 versus a total number of patents of 169,134. Hence, utility patents constitute more than 90 percent of all patents. As with the total patent count, we use the annual number of utility patents granted by the USPTO for a country as a measure of the level of domestic innovation activity existing within that country.

# **USPTO Utility Patent Citations Received**

It is widely accepted that innovations tend to vary enormously in terms of their technological and economic importance, significance, or commercial value. While the patenting process requires innovations to be assessed for their novelty and commercial value, patented innovations still tend to exhibit a large variance in terms of quality and economic importance. One method of accounting for the large difference in the quality and value of patents is to use patent citation data that are included in the details of each patent. These citations are to previous patents and to the scientific literature, and they enable the tracing of multiple linkages between inventions, inventors, firms, geographical locations, etc. In particular, citations received may be telling of the importance of the cited patent and thus the number of citations an individual patent receives acts as a simple indicator of the significance of cited patents, this allowing one to capture the enormous heterogeneity in the value of patents.

The idea of using patent citations to control for the quality of patented innovations has been
Figure B.2. Synthetic Controls: Effect of Gujarat Riots on Women’s Marriage Before Age 18 <!-- Start of picture text --> 1990 1995 2000 2005 2010 2015<br>year<br>gujarat synthetic gujarat<br>.5<br>.4<br>.3<br>child_marriage<br>.2<br>.1<br><!-- End of picture text --> _Note_ : This figure plots the estimates using synthetic controls approach and NFHS-IV. The outcome variable is the fraction of women who got married before age 18.

34
Data from SEDLAC show that between 1992 and 2002 (the highest point for a comparable data spell) the Gini coefficient for the distribution of household per capita income increased from 0.450 to 0.533.<sup>14</sup> Gasparini and Cruces suggest that during this period the increase in inequality was due the increase in the skills premium: put simply, the wage gap between skilled and low-skilled workers rose. The increase in the skill premium was associated with the modernization of production and organizational structures. This skill-biased technical change, in turn, was associated—to a certain extent—with Argentina’s trade and investment liberalization.

Another factor behind the rise in earnings inequality was the weakening of labor unions. There is evidence that labor union membership and activity diminished significantly from 1991 to 2001. The decline in union activity coincided with reforms such as the privatizations, trade liberalization and price stabilization of the 1990s, which reduced the power of unions through the dissipation of rents from state-owned enterprises, protective tariffs and inflation-induced rents. The decline in union activity during the 1990s, unsurprisingly, coincided with a period of rising wage inequality.

After the 2002 crisis, the Gini coefficient fell from 0.533 in 2002 to 0.442 in 2010.<sup>15</sup> The reduction in inequality accounted for 40 and 50 percent of the decline in extreme and moderate poverty, respectively (Figure 3). During this period, both labor income and non-labor income inequality declined. Gasparini and Cruces argue that the fall in labor income inequality can be accounted for by the expansion of employment generated by the fast economic recovery, the shift in favor of more low-skilled labor-intensive sectors as a result of the devaluation of the Argentine peso, the fading out of the effect of skill-biased technical change in the 1990s, and the rise in the influence of labor unions. All these factors caused the skills premium (measured here by the relative returns to tertiary education) to fall (Figure 6).

This period
(2020)<sup>14</sup> , the indirect standardization was calculated using 2020 both-sex mortality from the United States as the standard mortality schedule 5Mxs by three 5-year age groups consisting of ages 85-89, 90-94, and 95-99. We define the share of each population _k_ for each group cx,k such that 1 = ∑x cy,k, summing up over the three 5-year age groups and where the shares for the United States age structure are referred to by cx,R. The adjustment for population _k_ is as follows: These adjustment factors were multiplied by the observed age-specific COVID-19 mortality rates (and separately the estimated age-specific excess mortality rates) for the open interval 85+.

The coefficients, βi , are the rates of increase per year of age in probability of death. This calculation was performed first defining D(x, i) in terms of official COVID-19 counts by age for each country for which data was available. The calculation was also performed for each country defining D(x, i) using excess mortality estimates by age as described in the previous section.<sup>3</sup> These results provide 1) the slope of the COVID-19 age-mortality curve according to official counts, and 2) the slope of the age-mortality curve for excess deaths.

# **Results**

The left side of Figure 2 shows the age distribution of officially recorded COVID-19 deaths in 2020 by country along with the age distribution of excess deaths. According to official reports , on average across high-income countries, just 11 percent of deaths were among those under age 65.<sup>4</sup> In contrast, people under 65 constituted on average 40 percent of official COVID-19 deaths in upper-middle-income countries and 54 percent of deaths in lower-middle-income countries. The same pattern is observed using the distribution of excess deaths by age, shown on the right side of Figure 2. In high-income countries, those under 65 are also 11 percent of excess deaths. For the upper-middle-income countries for which
assessments indeed seem to increase the employability of out-of-job workers by giving them a certificate to prove their skills.

The end-line survey also asked those who became newly employed in the past six months (that is, since the baseline survey) how they found those jobs. Broadly, two job search channels are available to job seekers to find employment: formal and informal. Going through formal job search channels means searching and finding jobs through the publicly open job-posting information, traditionally in newspapers and increasingly on websites. Informal channels are through personal networks—typically family and relative networks. Using such informal job search channels is extremely common in Bangladesh, especially for micro and small companies. Naturally, formal job search channels tend to be more competitive and rely on proper documents of applicants’ qualifications. Going through informal channels may give job seekers lesscompetitive, flexible access to jobs, but the downside is that it keeps wages lower than they would otherwise be.<sup>9</sup> The survey results show that recent successful job seekers in the treatment group are significantly more likely to use formal channels to find jobs than their control group counterparts (see figure 3.2). It may well be because they are more confident and competitive in the open job market thanks to their RPL certificates. Also, among the RPL participants who found new jobs in the past six months, most (81 percent) said in the interview that the RPL assessment helped them a lot to find the job. These findings concur with the notion that RPL assessments and certificates enhance workers’ employability and confidence in skills, which would lead to improved employment outcomes for RPL participants.

**Figure 3.2 Job Search Channels Used by RPL Applicants Recently Employed at End-line**

<!-- Start of picture text --> Informal channel Formal channel<br>(personal networks) (digital/paper job postings)<br>88%<br>73%<br>27%<br>12%<br
ECOWAS‘S INFRASTRUCTURE: A REGIONAL PERSPECTIVE

**Table 2.4  Comparative performance across West African railways (2005)**

||Labor<br>productivity|Locomotive<br>productivity|Carriage<br>productivity|Wagon<br>productivity|Average<br>passenger<br>yield|Average<br>freight<br>yield|
|---|---|---|---|---|---|---|
|Benin, OCBN|40|3|900|74|2.0|5.8|
|Burkina Faso – Côte d‘Ivoire, SITARAIL|481|35||1,020|3.3|5.5|
|Ghana, GRC|84|7|416|458|2.4|4.4|
|Mali – Senegal, Transrail|339|40||804|2.2|6.4|
|Nigeria, NRC|37|13|737|59|─|─|
|SSA average for railways under<br>concession|387|24|2,945|510|2.2|6.3|

Legend: Labor productivity = ̳000s traffic units per employee; Locomotive productivity = millions of traffic units per locomotive; Carriage productivity = ̳000s passenger-kilometers per carriage; Wagon productivity = ̳000s net tonne-kilometers per wagon. Source: AICD railways database.

# Ports

Container and general cargo traffic moving through West Africa‘s ports increased substantially between 1995 and 2005. The annual average growth in container traffic was even higher than in other parts of Africa, whereas growth in general cargo, however substantial, was not as rapid as in southern Africa (table 2.5). Overall growth in containerized traffic growth was propelled by rapid economic growth in Sub-Saharan Africa, a rising tide of global trade, the privatization of ports, and the advent of modern container vessels.

With
# **1 Introduction**

Epidemics and pandemics, including the Coronavirus Disease 2019 (COVID-19), have large impacts on human life and livelihoods. The 1918 influenza, for example, caused large declines in economic output as many productive workers died (Fenske, Gupta, and Yuan 2020; Tumbe 2020). During a pandemic, governments typically intervene to slow its spread, as well as to mitigate the economic impact and revive activity. Thus, understanding the impact of government restrictions on reviving or hindering economic activity is important.

This paper estimates the impact of differential containment policies implemented by the Government of India (GoI) during the COVID-19 pandemic on aggregate economic activity. The first COVID-19 infection in India was reported at the end of January 2020. In March, the GoI implemented one of the most stringent lockdowns globally (Hale et al. 2020). After five weeks of nationwide lockdown, uniform restrictions were replaced with targeted measures that introduced variation across districts in May. The differential relaxation of restrictions across districts permits us to examine the impact of the heterogeneous containment measures. Districts were classified into three zones: those with the most severe restrictions (Red), those with intermediate restrictions (Orange), and those with the least severe ones (Green). Using a difference-indifferences approach, we compare the speed of recovery in the three zones after the uniform national lockdown. Using monthly data of man-made nighttime lights at the district level, we examine the impact of these differential relaxations of restrictions on aggregate economic activity. We also examine the period after the differential lockdown to understand whether the containment measures yielded subsequent gains in economic activity. We validate and explain the aggregate impact by analyzing mobility patterns across districts and household income and consumption. In addition, we compare the impact across different districts by accounting for their population density, the share of services sector employment, outstanding credit per capita, and the average age.

We use nighttime light intensity as our main proxy of economic activity for a number of reasons. First,
# _2.8 Summary of Findings and Recommendations_

Creditor protection through modern secured transactions legal regimes is associated with higher ratios of higher private sector credit to GDP. **Increasing the protection of creditor’s rights and enforcement mechanisms can lead to a considerable increase in private sector credit to GDP** .<sup>45</sup> As evidenced by numerous sources of data such as the World Bank Enterprise surveys, the Legal Rights Index of the Doing Business Report and the recent World Bank MENA SME Lending Survey, the MENA region lags clearly behind the rest of the world in firms’ access to private credit and in the robustness of secured transactions systems.

In the World Bank’s Enterprise Surveys, **the MENA region had the lowest percentage of firms with credit lines or loans from financial institutions** , at 25.07%, compared to 56.92% for Eastern Europe and Central Asia (ECA), 54.97% for Latin American & the Caribbean (LAC), and 45.02% for South Asia. Moreover, enterprise survey data from 7 countries in MENA points out that **collateral requirements for firms requesting loans are substantial** . On average, 82% of loans require some type of collateral. Improving secured transactions regimes has helped alleviate this constraint in other countries and can reasonably be expected to do the same for the MENA countries.

# **Modern and efficient secured transactions systems have the objective of facilitating lending**

**to firms** , especially SMEs by creating the conditions for firms to be able to use movable property as collateral for loans. Modern secured transactions systems are built around the **following principles or pillars** :

- **Scope:** the types of legal structures that can be used to secure obligations (e.g. security interest, pledge, mortgage, etc.); the types of transactions that should be considered within the scope of the law (loans secured with movable property
# **Incentivizing Calculated Risk-Taking: Evidence from an Experiment with Commercial Bank Loan**

Shawn Cole Martin Kanz Leora Klapper<sup>_∗_</sup> July 23, 2012

**Abstract**

This paper uses a series of experiments with commercial bank loan officers to test the effect of performance incentives on risk-assessment and lending decisions. The paper first shows that, while high-powered incentives lead to greater screening effort and more profitable lending, their power is muted by both deferred compensation and the limited liability typically enjoyed by loan officers. Second, the paper presents direct evidence that incentive contracts distort judgment and beliefs, even among trained professionals with many years of experience. Loans evaluated under more permissive incentive schemes are rated significantly less risky than the same loans evaluated under pay-for-performance.

**EPOL, FSE JEL** : D03, G21 J22, J33, L2 **Keywords** : loan officer incentives, banking, emerging markets

> _∗_ Harvard Business School; World Bank Development Economics Research Group and World Bank Development Economics Research Group, respectively. E-mails: scole@hbs.edu, mkanz@worldbank.org, and lklapper@worldbank.org. We wish to thank the cooperating financial institution for providing us with the data on loan applications used in this paper. For helpful comments and suggestions, we thank Philippe Aghion, Andreas Fuster, Victoria Ivashina, Raj Iyer, Michael Kremer, Rohini Pande, Jose Liberti, Daniel Paravisini, Enrichetta Ravina, Andrei Shleifer, Antoinette Schoar, Erik Stafford, Jeremy Stein, and conference and seminar participants at Bocconi (Carefin), University of Chicago (Advances with Field Experiments), IGIDR Mumbai, IIM Bangalore, FIRS (Minneapolis), LBS European Winter Finance Conference 2012, NBER Corporate Finance, NBER Risks of Financial Institutions, University of Virginia (Darden), and the World Bank. Samantha Bastian, Doug Randall, and Wentao Xiong provided excellent research assistance. Financial assistance from the Kauffman Foundation, the International Growth Center, and the Harvard
of vulnerability: (i) the physical propensity to experience severe income, asset or health loss and (ii) the inability to cope with and recover from the losses. Multiple dimensions are considered within each of these. We introduce the proposed indicators for measuring each dimension.

### Physical propensity to experience severe loss

Access to electricity and a certain standard of drinking water are critical for economic activity and survival and as such are included in the World Bank’s multidimensional poverty measure (World Bank 2018). Additionally, when shocks hit, access to these services is an important determinant of the impact of the shock on welfare. For example, with access to improved drinking water, contaminated water from flooding and storms, or lack of water due to drought has less of an impact. Nevertheless, it is essential to acknowledge that the current indicator of access to improved drinking water, often represented by covered wells in low-income countries, may not sufficiently reflect susceptibility to contamination during extreme events such as floods or droughts. Therefore, there is a need for future work to refine this indicator by considering a potentially higher threshold. Metrics such as “improved piped water” can offer a more precise assessment of the infrastructure safeguarding against water-related risks in the event of shocks. With access to electricity, households are more likely to have assets such as fans that can help with heatwaves. A fuller discussion is available in the World Bank’s Lifelines report (Hallegatte et al, 2019). Whilst not a final selection of assets and infrastructure that matter for determining the initial loss of the shock, these measures provide a good first estimate to stimulate discussion. Access to markets and 15
fund social services and infrastructure and finished with the TRA’s slogan “Together we build our Nation.” Treatment 3 included the simple reminder as well as a ’social pressure’ message in which taxpayers were reminded, in a negative fashion, that non-compliers were not contributing to the development of the country or their own communities. The final planned treatment was an enforcement message which included the simple statement “Pay your tax early to avoid penalties.” However, for reasons we discuss below, during the implementation of the experiment no taxpayers were sent this message.

# **3.3 Implementation and challenges**

Following the randomization, a list of taxpayers and their phone numbers (included in the original TRA dataset) were provided to the TRA. The majority of messages were sent out after June 20, fewer than ten days before the initial deadline to pay property tax. While there was overlap in the delivery of different treatments, completion of each treatment arm proceeded sequentially, with reminder messages being sent first to group T1, reciprocity messages second to group T2, followed by social pressure messages to group T3.<sup>4</sup> There were two errors in the message delivery process. First, the firm in charge of sending the messages sent Treatment 1 messages to taxpayers who had been randomly allocate to Treatment

> 3The randomization was conducted using the Stata command `randtreat` , with “misfits” (i.e., observations beyond those that are a multiple of the number of treatment groups) being dealt with using the _strata_ method, which randomly allocates misfits across all strata (Carril et al. 2017).

> 4Figure A1 in the Appendix shows the timing of message delivery. One concern is that the differential timing of message delivery affected the impacts. In the results section, we provide suggestive evidence that our pattern of results is robust to this.

5
Ahmad et al., 2023), we find that providing information and access to indoor air quality monitors (IAQMs) does not change households’ willingness-to-pay for either IAQMs or indoor air purifiers.

To examine the extent of infiltration in Tbilisi, we combine the data from the indoor air pollution monitors with the nearest outdoor monitors and estimate the rates of infiltration of outdoor pollution indoors. Results show that infiltration rates in Tbilisi exceed estimates from the U.S. by approximately 2-4 times (Lunderberg et al., 2023). Compared to the U.S very high infiltration is more common, which may be due to a lower average quality of housing. However, variations in infiltration rates seem to be mainly driven by short-term behavioral differences (e.g. length of time 3
Learning from Developing Country Power Market Experiences: The Case of Philippines <!-- Start of picture text --> GWh<br>70,000 45%<br>Spot market<br>(GWh) 60,000 40%<br>16% 35%<br>50,000<br>30%<br>40,000 25%<br>30,000 20%<br>Bilateral 20,000 15%<br>contracts 10%<br>(GWh) 10,000 5%<br>84%<br>0 0%<br>2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017<br>Bilateral contracts (GWh) Spot market (GWh) Relative size of spot market (%)<br>Figure 5‐1 Relative size of power submarkets in<br>Figure 5‐2 Evolution of traded energy volumes in contracts and spot<br>Philippines during 2017, as percentage of total traded<br>market in Philippines.<br><!-- End of picture text --> Figure 5‐1 Relative size of power submarkets in Philippines during 2017, as percentage of total traded energy.

Source: Own elaboration based on data collected by the World Bank.

Source: Own elaboration based on data collected by the World Bank.

Contracted electricity volumes are driven by load growth (around 85‐95% of customer loads are permanently contracted by most Discos). Maturity is usually long‐term (typically 20 yrs.) for coal‐fired power plants, and short to medium‐term (e.g. 5‐10 yrs.) for peaking plants and also for other existing plants (e.g. coal, geothermal and hydro). On the other hand, absent a spot market, peaking plants in Mindanao are bilaterally contracted with a typical maturity of 20 years. Regulated contract prices are based on actual generation costs.

Energy traded in