rafmacalaba/data-use-mentions-extended huggingface dataset:
: Central Banking News, Haver Analytics, International Monetary Fund. A. “Balance” stands for fiscal balance and reflects the unweighted average of 89 commodity‐exporting and 62 commodity‐ importing EMDEs. “Debt” stands for general government debt and reflects unweighted average gross government debt of 86 commodity‐exporting and 61 commodity‐importing EMDEs.

B. Figure includes 22 commodity‐exporting and 18 commodity‐importing countries with a stated inflation target and for which current inflation data is available. Latest observation is for Nov 2016.

# **Figure 18. Infrastructure, education, and health investment needs**

_Substantial gaps in infrastructure, education, and health investment needs remain across the world._

## **A. Global infrastructure investment gap**

<!-- Start of picture text --> Percent of global GDP 0.58 3.5<br>0.71<br>0.75<br>1.01 0.27 0.04 0.12<br>Roads Rail Ports Airports Power Water Telecom Total<br><!-- End of picture text --> Sources: UNCTAD (2014), World Bank (2016b), World Bank estimates. A. The figure shows global investment in infrastructure (as percent of GDP) required over 2015‐30, as projected by McKinsey Global Institute.

B. Investment refers to capital expenditure. Upper bounds for the estimated investment needs are reported. Red column denotes 2014 or latest available year. SDG refers to the United Nation’s Sustainable Development Goals.

38
conclusions 34 of a risk assessment — hazard, exposure, and vulnerability — a fourth component, socioeconomic resilience. Like the traditional components of risk management, socioeconomic resilience can be measured at any degree of spatial resolution, from the household to national averages.

Using a new agent-based model that represents explicitly the recovery and reconstruction process at the household level, this risk assessment provides more insight into flood impacts in Sri Lanka than a traditional risk assessment. In particular, it shows how the regions and communities identified as priorities for risk-management interventions differ depending on which risk metric is used. While a simple costbenefit analysis based on asset losses would drive risk reduction investments toward the richest regions and areas, a focus on poverty or wellbeing rebalances the analysis and leads to a set of priorities to integrate DRM into the larger development agenda.

In parallel, measuring disaster impacts through poverty and wellbeing implications helps quantify the benefits of interventions that may not reduce asset losses, but do reduce their wellbeing consequences by making the population more resilient. These interventions include financial inclusion, social protection, and more generally the provision of post-disaster support to affected households.

The model and data used in this analysis have many limitations. For instance, the 2016 HIES is only statistically representative at the district level and does not offer the geolocalization of households. Further, the SSBN model is itself a complex and imperfect exercise. Finally, the model does not represent all coping mechanisms available to households, such as international remittances or temporary migrations. However, even with these limits and simplifications, the introduction of socioeconomic resilience and household characteristics into risk assessments provides actionable insights and appears as a promising research agenda.
for writing (25 percentage points), math (17 percentage points) and computers (33 percentage points), but found no significant relationship between wages and computer _skills_ at work. They inferred that higher wage premiums are associated with computers _if_ computers are used in an advanced manner.

More recently, Falck et al. (2016) used PIAAC data from 19 countries to estimate labor market returns of information and communication technology (ICT) skills. Starting with the premise that developing such skills is facilitated by internet access, the authors employed an instrumental-variable strategy based on variation in broadband internet access—and found that a one stand deviation increase in ICT skills increased earnings by 24 percent.

Overall, the existing research on wage premiums related to cognitive and noncognitive skills, as measured by reading proficiency levels, frequency and complexity of computer use on the job, and personality traits and selected behaviors, shows some consensus on the role of these skills in predicting labor market success. The size and magnitude of these relationships vary and are in many ways a function of the range of metrics used to proxy for cognitive and noncognitive skills.

7
data for other non-bank financial service providers (such as credit unions, cooperative, finance companies, and microfinance institutions), which are often not regulated.

Using data gathered through our survey of bank regulatory bodies and from other sources, we put together the following indicators of banking sector outreach:<sup>7</sup>

- 1- Geographic branch penetration: number of bank branches per 1,000 km<sup>2</sup>

- 2- Demographic branch penetration: number of bank branches per 100,000 people

- 3- Geographic ATM penetration: number of bank ATMs per 1,000 km<sup>2</sup>

- 4- Demographic ATM penetration: number of bank ATMs per 100,000 people

- 5- Loan accounts per capita: number of loans per 1,000 people

- 6- Loan-income ratio: average size of loans to GDP per capita

- 7- Deposit accounts per capita: number of deposits per 1,000 people

- 8- Deposit-income ratio: average size of deposits to GDP per capita

Indicators (1) through (4) measure the outreach of the financial sector in terms of access to banks’ physical outlets. The data for each of these indicators, across 98 countries in the case of branches and 89 countries in the case of ATMs, are shown in Table I. The indicators of branches and ATMs per square kilometers help characterize the geographic penetration of the banking sector. They can be also interpreted as proxies for the average distance of a potential customer from the nearest physical bank outlet. Higher geographic penetration would thus indicate smaller distance and thus easier geographic access. Per capita measures of branches and ATMs are used to capture the demographic penetration of the banking sector. They proxy for

> 7 In previous versions of the paper, we reported combined indicators, such as principal component indicators combining the geographic and demographic penetration of branches or ATMs and residuals of a regressions of branches/ ATMs on area and population.  However, unlike the indicators
129 countries and 749 goods, after dropping some regions and countries with limited coverage or no mapping with exchange rate data and special SITC codes used by Feenstra et al. (2005) to make 4-digit ows compatible with 3-digit values. In particular, all countries exporting less than 10 4-digit SITC commodities and all commodities exported by less than 10 countries are excluded, as well as the US, which is the country of the anchor currency. Country-commodity pairs where the correlation between international prices and exchange rates was constructed using less than 8 annual observations or those with a correlation larger than 0.9 (in absolute value) were also dropped. Using this dataset the export shares of a country in dierent goods was constructed as described in the previous section. The countries included in our main sample as well as their average exports at SITC level, and number of goods exported are reported in the appendix.

The international price of a good _Pi,t_ is measured by its global unit value, using data on total values and quantities exported across the world, also from the Feenstra et al. (2005) database, where _Vi,t_ is the total value of global gross exports of good _i_ , and _Qi,t_ is the total global quantity exported (in tons). The price index built in this manner corresponds to a quantity weighted average of country-level unit values.

Despite is simplicity and wide availability there are several shortcomings in using unit values as measures of international prices, most importantly that they do not control for changes in quality. Thus, an increase in the quality of goods could result in an increase in unit value that should not be captured by an ideal price index that controls for the characteristics of a good. However, since this paper focuses on global unit values, this would not be a problem if the average quality of traded goods across the world does not change signicantly. Although there is no evidence on this regard, the average quality of exported goods is more likely to be stable
WPS3826

# Incomplete Contracts and Investment: A Study of Land Tenancy in Pakistan

## Hanan G. Jacoby∗ Ghazala Mansuri∗

### Abstract

When contracts are incomplete, relationship specific investments may be underprovided due to the threat of opportunistic expropriation or holdup. This paper finds evidence of such underinvestment on tenanted land in rural Pakistan. Using data from households cultivating multiple plots under different tenure arrangements, the paper shows that land-specific investment is lower on leased plots. This result is robust to the possible effects of asymmetric information in the leasing market. Greater tenure security also increases land-specific investment on leased plots. Moreover, variation in tenure security appears to be driven largely by heterogeneity across landlords, suggesting that reputation may be important in mitigating the holdup problem.

Keywords: Incomplete Contracts, Holdup, Land Tenancy JEL: L14, D82, O12

## World Bank Policy Research Working Paper 3826, February 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._

> ∗Development Research Group, World Bank, 1818 H St. NW, Washington DC 20433. Jacoby (corresponding author) e-mail: hjacoby@worldbank.org; Mansuri e-mail: gmansuri@worldbank.org. An earlier version of this paper circulated under the title "Incomplete Contracts and Investment: A Study of Land Tenancy in Pakistan."
**Figure 2. Minimum-to-median and minimum-to-mean wage ratio, Romania and selected OECD countries a. Romania, 2007-2023**

<!-- Start of picture text --> 70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023<br>MW, as % of Mean MW, as % of Median<br>Percent<br><!-- End of picture text -->

# **b. OECD countries and selected non-OECD countries, 2023**

<!-- Start of picture text --> 100<br>90<br>80<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>MW as a % of mean wage MW as a of median wage<br>Percent<br>Colombia Costa Rica Chile Mexico Portugal New Zealand Türkiye Slovenia France Korea United Kingdom Luxembourg Romania Australia Poland Spain Germany Slovak Republic Israel Canada Bulgaria Greece Netherlands Belgium Ireland Hungary Lithuania Japan Croatia Czechia Estonia Latvia United States<br><!-- End of picture text --> _Source: Own estimates based on OECD data, available here: OECD data explorer Note: This indicator represents the_ _<mark>ratio</mark>_ <mark>of</mark> _<mark>minimum wages in relation to the me</mark> an and_ _<mark>median earnings of full-time employees. Using median earnings, as opposed to mean earnings, offers a more accurate basis for international comparisons by accounting for variations in earnings dispersion across different countries. The median is also less affected by extreme values (outliers) in the data compared to the mean. Outliers, which can be unusually high or low values,
|93%|

_Sources: Innovation for Poverty Action (IPA, 2020) and Gourlay et al. (2021). Based on survey round 1 in each country. The IPA Recovr surveys used random digit dialing of a nationally representative sample of phone numbers._ For the HFPS surveys, we can further diagnose the observed patterns of nonresponse. Figure 3 displays response rates from five countries broken down by urban/rural and agricultural/nonagricultural status. The response rates in Uganda, which are very high, benefitted from the relatively recent pre-COVID inperson survey which allowed for an updating of contact information shortly before implementation of the 8
the price response.<sup>57</sup> Alternatively, this implies that programs that provide in-kind transfers, such as The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC), would enable beneficiaries to receive the full benefit. However, this advantage must be weighed against the disadvantages of providing in-kind transfers, which could include shifting the price effect onto the government, limiting consumer choice, and leakages. Second, supply-side interventions in neighborhoods with

> 55Theoretically, Cowan (2004) shows that under imperfect competition such as monopoly and symmetric Cournot oligopoly, the quantity response can be negative for an increase in demand, depending on the curvature of demand.

> 56Thomassen et al. (2017) provide empirical evidence by applying a novel demand model to UK consumer data and find that product categories are complements due to shopping costs.

> 57Suppose an experiment raising benefits per population by 1%. This raises the price of food by 0.0724%, but since this cuts into the spending power of 100% of benefits, the real spending power of the marginal benefit gets reduced by 7.24%. The same logic applies to the case of extrapolating to inframarginal changes.

33
our assessment tool<sup>9</sup> , and two, to provide a benchmark for how enforced standards might improve reporting. Articles in medicine were drawn from the top three medical journals according to impact factor in general and internal medicine on July 6th, 2010, from Thompson Journal and Citation Reports (Thompson Reuters 2010). These were _The_ _Lancet_ , _The Journal of the American Medical Association_ , and _The New England Journal of Medicine_ . This restriction was made for ease of processing, as it reduced the number of eligible studies in each year from several thousand to approximately 350, and to ensure we were evaluating the “gold standard” in medicine as described above. The selection process for medical articles was as follows:

1. We searched Pubmed (a database similar to Econlit indexing articles in medical journals) for all articles reporting clinical trials in the three journals in years for which there was also an eligible economics article (all years in our range save 2002).

2. From this list, we then randomly selected as many articles in a given year as there were eligible articles in economics from that year. Among studies published in a given year, selection was performed by assigning each article a random number between 0 and 1 using a random number generator. We sorted the articles by their randomly assigned number and, beginning with the lowest random numbers, we then selected the required number of articles.

3. We excluded phase one and phase two trials in medicine as their methods, goals and sample size considerations are significantly different from phase 9. Given that the medical trials we collected were published in journals that required adherence to the standards in the CONSORT Statement, if we were to find most medical trials were at high risk of many biases (low risk of all biases), we would be concerned that the instrument was too strict (lenient).

25
SNA, which is valid to date. However, since the 1993 SNA, countries have been encouraged to measure own-use services under the (wider) SNA _general_ production boundary. This information is sometimes compiled in satellite accounts, as an annex to the national accounts (OECD 2002; Esquivel 2011).

In the realm of labor force statistics, the 13<sup>th</sup> ICLS in 1982 defined the “economically active population” as “all persons who furnish the supply of labor for the production of economic goods and services as defined by the United Nations systems of national accounts and balances” (ILO 1982: par. 5). Explicitly included was “all production and processing of primary products, whether for barter in the market or for own consumption” (ILO 1982: par. 5). The revised ICLS standards, by narrowing the concept of employment to “work performed for pay or profit”, not only revised previous labor statistics standards, but also broke the previous congruence between employment and the SNA production boundary. In addition, the 19<sup>th</sup> ICLS standards introduced a new concept of “work”, which captures all activities within the SNA _general_ production boundary (see below for further discussion).

# **_Why a new definition of employment?_**

The 19<sup>th</sup> ICLS sought to address multiple concerns with the 13<sup>th</sup> ICLS standards. Among them was the notion that the previous definition of employment, by combining work for pay or profit with own-use production work, was too broad and therefore limited the usefulness of employment statistics as an indicator of labor market performance. Similarly, the previous concept of unemployment was perceived as too narrow, since farmers producing for family use and other individuals performing own-use production work, by virtue of being considered as employed, were ineligible for classification under unemployment (ILO 2013a).<sup>6</sup> By narrowing
45 Note: The starting point was our database of 33,000 publications in EconLit with a health JEL code. Google Scholar citation data were obtained for as many as possible (80 percent) in June 2011. Each listed institution was given full credit for a publication in the case of a co-authored publication, but only the first institution was credited where an author listed multiple institutions. Institutional affiliations below the institution level were aggregated up to the level of the institution, so that for example publications originating from the Harvard School of Public Health were allocated to Harvard University along with publications originating from the Department of Economics at Harvard University. As explained in the text, only addresses with five or more articles to their name were retained for cleaning and aggregating. An _h_ -index of 10 means that the author has 10 publications to his or her name each of which has been cited at least 10 times. The quadratic influence function is defined in eqn (1). The measure _I_<sup>3</sup> is defined in eqn (2).
**Notes** : This table presents the descriptive statistics from the budget execution dataset. The variables “Distinct commitments”, “Distinct verifications” and “Distinct payments” are simply the count of the identifiers that uniquely identify each table - _empenho_ , _liquidacao_ , _pagamento_ . In the states of CE, PB and PE we can not count the number of distinct verifications because we were unable to build a unique identifier for this table. Likewise for distinct commitments and distinct payments in the case of PE. The variables “Has verification information” and “Has payment information” refer to the percentage of commitment identifiers with any verification or payment information, respectively, in the current year or later. This means that they can be followed throughout the execution process. The state of PB has a low percentage of commitments with verification information due to different temporal coverage of those two tables - while the first starts on 2003, the later starts on 2008. The commitments related to procurement restricts the data to three categories: consumption material (code 30), material for free distribution (code 32) and, equipment and permanent material (code 52). Also, the number of distinct sellers is missing for PE because we don’t have information about suppliers in the payment table. The variable “Total amount of payments” is in 2021 prices.

33
currency-based approaches to estimate the growth of domestic vis-à-vis international bond issuances. The results are robust to using these two alternative measures.

For some parts of the analysis we use equity and syndicated loan data, which also come from SDC. The equity data include 43,196 issuances by 13,860 firms (Table 1, Panel B). We classify equity issuances into domestic and international using the residence-based approach. We use syndicated loans because, unlike typical bank loans, they are available for all economies. Moreover, syndicated loan markets capture a sizable share of bank financing and are the most relevant comparison to capital markets in terms of transaction size (amount raised per issuance) and terms of financing, such as debt maturity (Ivashina and Scharfstein, 2010; Cerutti et al., 2015). The syndicated loan data include 25,493 issuances by 9,606 firms (Table 1, Panel C). To distinguish between domestic and international (crossborder) syndicated loans, we compare the nationality of the lead bank that arranges the deal with the residence of the issuing firm. Domestic loans are those in which only domestic banks lead the syndication, whereas international syndicated loans entail the participation of at least one foreign bank acting as a lead arranger.

# _2.3. Firm Size Measure and Firm-level Data_

To study the types of firms issuing in domestic and international markets, we focus on size. We follow the literature that typically uses firm size or collateral to measure access to debt across markets, firms, and over time (Pagano et al., 2002; Beck and Dermirguc-Kunt, 2006; Claessens and Schmukler, 2007; Beck et al., 2008; Campello and Larrain, 2016; de la Torre et al., 2017).

The literature on firms’ issuance activity tends to study the size of issuers through balance sheet data using, for example, firms’ assets.<sup>5</sup> The downside of this approach is that balance sheet data

> 5 See, for
|48.5|
|Middle|19.0|23.9|24.2|22.9|24.94|26.04|
|Southern|46.7|37.5|34.2|38.4|25.4|25.5|
|_All Urban_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|_100.0_|

Source: NCS, 1985/86 and 1992/93.

Tables 4.10 and 4.11 show the poverty incidence indicators by agroclimatic zones. In 1985, 54.9 percent was poor in rural north and 34.2 percent in urban north. In 1992, the corresponding figures are 44.2 percent and 40.3 percent respectively. The Southern region classified into Southwest and Southeast is very illuminating. Poverty in the cocoa producing rural Southern regions is the lowest. This comes out convincingly in Table 4.11, where rural Southwest contributes the least to national rural poverty with 17.1 percent in 1985 and 15.3 percent in 1992. Even in urban areas, the Southwest decline in poverty incidence is very pronounced. In terms of depth and severity of poverty, Southwest is performing well. Except for rural Southeast, where poverty severity has worsened over the seven year period, all indicators of agroclimatic zones show a general trend of improvement.

Table 4.12 shows the evolution in poverty measures, by state. Taking the head count (P0) first, the table shows that Gongola, Cross River and Sokoto are the only states that show an increase in head count index of poverty during 1985/86-1992/93. The sharpest decline in head count (26%) was for the state of Bendel, Cross Rivers, Sokota are the states indicating an increase in the depth (PI) of poverty. Six states however, show an increase in severity (P2 ) of poverty during the seven year period of this study.