rafmacalaba/data-use-mentions-extended huggingface dataset:
and rural wages and income composition in the last decade. Section 3 analyzes wage determination and differences in returns across the wage distribution. Section 4 addresses correlates of nonfarm employment and the likelihood of being employed in the high/lowproductivity sectors. Finally, Section 5 concludes and gives policy recommendations.

# **2. Rural Labor Markets**

The Mexican rural labor market is important for poverty reduction. Employment is key to lifting poor rural families out of poverty. The rural labor market can be analyzed in many ways. One way is to consider the agriculture and nonagricultural sector or off-farm sector. Rural off-farm employment has traditionally been seen as a low productivity sector, producing low quality goods. The sector, in this view, is expected to shrink as the economy develops and incomes increase. However, recent research shows that this view can be very socially costly. For example, the rural nonfarm sector has a positive role in absorbing a growing rural labor force and slowing rural-urban migration. Moreover, the nonagricultural sector contributes to national income growth and to promote a more equitable distribution of income (see Lanjouw and Lanjouw 2001).

Lanjouw and Lanjouw (2001) also finds that the nonagricultural sector is large and growing in developing countries. In Latin America alone, 47 percent of the labor force in rural settlements and rural towns are employed in off-farm activities. Moreover, 79 percent of women in the Latin American rural labor force are employed in off-farm activities.

Araujo, de Janvry and Sadoulet (2003) measures the role of social networks on behavior applied to rural off-farm employment in Mexico. The authors find that income from off-farm sources is especially important for rural households, and explore the determinants of participation in off-farm nonagricultural employment using data for rural Mexico. In particular, they seek to understand the role of social networks on the individual decision to participate in off-farm labor markets. Araujo et al. find that neighbors' participation in off-farm nonagricultural employment has a significant impact on the individual choice of occupation, even after controlling for availability
Second, regarding technical risk, in addition to the risk of going beyond the plant‟s own expertise, another important question concerns the intrinsically higher sophistication of product innovations, especially when they are of a more radical nature. Thus, introducing a product that is new to the plant and to the country (i.e., that no other plant has introduced before) is likely to be more risky than introducing a product that is new only to the plant. Columns (7)-(9) of Table 7 show the results from estimating our main specifications considering separately product innovations that are new to Chile and those that are new only to the plant. Both types of product innovations increase survival odds of Chilean plants and the t-tests show that the effects are not significantly different. A different way to capture technical risk is to consider the degree of sophistication of the new products introduced by Chilean plants, under the assumption that the higher is that degree the more risky is the innovation potentially. We use a trade-based proxy to measure the sophistication of each product following Hausmann et al. (2007) and its application by Jarreau and Poncet (2012). The proxy, described in detail in Appendix 3, gives a larger score indicating higher sophistication to products that are mostly exported by countries with higher GDP per capita, thus inferring from observed trade patterns the products that require greater levels of development to be exported. We estimate our main specifications splitting product innovations into those that are less versus more sophisticated. Columns (10)-(12) of Table 7 show that while the innovation-survival relationship is significant only for plants introducing less sophisticated product innovations, the t-tests indicate that the difference of coefficients is not significant. Again, a shortcoming of this approach is that the product sophistication measures do not cover all Chilean innovators due to difficulties in establishing concordances between the 7-digit ISIC level and the HS classification of the trade data.

We examine the third dimension of market risk by considering in Table 8 alternative measures of innovation
|0.10|37,918|6,143|1,723|1,162|116 **months**<sup>_e_</sup>|

The descriptive statistics are calculated using FEWS NET ratings, netted of humanitarian assistance effects, taking admin2 districts as the level of observation. “IPC Rating” refers to the netted data on the original 1-5 scale, while “Crisis Indicator” refers to the binary indicators of phases (3) and above. The data dimensions under “Coverage” refer to the number of admin2 districts in the country, disregard of whether all of these districts cover livelihood zones that receive ratings from FEWS NET, and the number of assessment periods from the first assessment to the last (February 2019). The June/October 2019 and February 2020 assessments are used only for validation and not included in this table. Further guidance on data coverage is as follows: _a_ partially covered, _b_ missing at random, _c_ latest assessment periods missing, _d_ earliest assessment periods missing,<sup>_e_</sup> from first to last assessment: July 2009 - February 2019.

# **2.2 Covariates of food crisis events**

We forecast transitions into food crisis using only readily-observable covariates, available monthly at the admin2 district level prior to outcomes. We deliberately do not use lagged 5
National Action Plan for implementing UN Security Council Resolution 1325 which calls for the greater involvement of women in all peace and security efforts.

Women in Sudan enjoy less than a third of the rights men do related to their economic opportunities, according to the World Bank’s WBL 2021 report. The report explores the legal differences in men’s and women’s access to economic opportunities, measured through a series of indicators across eight dimensions: mobility, workplace, pay, marriage, parenthood, entrepreneurship, assets, and pension. Data from 190 countries are examined going back nearly 50 years. Each country is provided an overall score that is an average of their individual score for each dimension, ranging from 0 to 100, with 100 representing the highest score (that is, there are no legal differences in men’s and women’s access to economic opportunities in the indicators measured). Sudan has an overall score of 29.4, and the only three countries that score lower than Sudan are Kuwait, with an overall score of 28.8; Yemen, with an overall score of 26.9, and the West Bank and Gaza, with an overall score of 26.3 (World Bank 2020d; World Bank 2021).

Over the last decade, Sudan has not seen any improvements in the dimensions measured, and it scores 0 on the dimensions of mobility, workplace, pay, and marriage. For example, the legal restrictions the 1997

> 11 The other countries that have not signed are the Holy See, the Islamic Republic of Iran, Somalia, and Tonga. The United States and Palau have signed but not ratified the treaty. Recent media coverage in Sudan suggests that Sudan may change its position with respect to the treaty.

23
with the absence rates from our survey to calculate both the STR and ESTR by state in 2003 and 2010 (Table 2 - columns 4-9). We see that though all-India STR had been reduced to below 40 in this period, the effective STR after accounting for teacher absence was over 52. The effective STR in 2010 in three of India’s most educationally backward states (Bihar, Jharkhand, and Uttar Pradesh) was as high as 97, 79, and 69. These figures illustrate that teacher absence can sharply increase the effective STR experienced by students relative to the STR calculated using state-level figures on enrollment and number of teachers.

# **3.3 Official Records, Teaching Activity, and Stated Reasons for Absence**

Enumerators recorded whether a teacher had been marked as present in the log-books on the day of the visit and also on the previous day, and we see in Table 3 - Panel A that going by these records would suggest a much lower teacher absence rate of 16 percent using the same day’s records, or as low as 10.2 percent using the previous day’s records (this was not collected in 2003). These data suggest that official records can be easily manipulated, and highlight the importance of measuring teacher absence by direct physical verification as opposed to official records on log books.

Enumerators also recorded the activity that teachers were engaged in at the point of observation, and we see that 53 percent teachers on the payroll were found to be actively teaching, and another 4 percent were coded as passively teaching (defined as minding the class while students do their own work). Just over 19 percent of teachers were in school but were either not in the classroom or not engaged in teaching activity while in the classroom. Thus a total of 42 percent of teachers on the payroll were either absent or not teaching at the time of direct observations (Table 3 - Panel B).<sup>15</sup> In cases where a teacher was not
lack of firm-level data on trade credit contract terms. Most studies have used the Federal Reserve‘s Survey of Small Business Finances (SSBF) database of U.S. firms, which has only limited data on credit terms and firm characteristics (e.g., Petersen and Rajan, 1997; and Giannetti et al., 2011). Ng et al. (1999), instead, uses survey level data on 950 listed U.S. firms to study the determinants and characteristics of trade credit contracts.

> 6 Unfortunately, we were unable to obtain repeated cross-sections or panels of data from Prime Revenue, because these are proprietary data. We obtained a single snapshot of data for the year 2005, prior to Prime Revenue starting factoring the receivables in 2006.

> 7 Buyer and supplier size buckets based on total sales are (in U.S. dollars): less than $0.1 billion; $0.1-2 billion; $2-7 billion; $7-10 billion; larger than $10 billion.

7
looks at the drivers of those departures from market integration and complete price transmission in India focusing on the spatial dimension.

This section explores the importance of six potential drivers of integration. These are transport costs, price adjustment dynamics (measured as the time it takes for shocks to be corrected), information frictions, the regulatory framework under which trade happens, commodity specific characteristics, state level production and regional consumption preferences.<sup>16</sup> To conclude, the costs of crossing state borders in terms of price differentials are explored. With India being a federal country, its states behave in several ways like separate countries, with state border authority checks on both parts of the border levying taxes, conducting road transport checks and imposing commodity specific taxes. To understand the impact of these barriers to trade across states on food prices, we examine whether, for a given distance between a pair of districts, deviations from market integration are larger when there is a state border between them. For these purposes we build on the “border effect” literature to estimate the cost of crossing borders in India. The section exploits the district level information from the wholesale price database. The specific question posed is if, for a given distance, the average price‐difference between any two pairs of districts is lower in the case that they belong to a common state.

The section is structured in three sections. The first section presents the details of the analysis as well as the database. The second section looks at the economic determinants behind the deviations from the law of one price in retail markets. The third section expands the analysis to wholesale markets and tests for the border effect.

# The Analysis

In this section we present the two databases that we use for the analysis. The database covers retail and wholesale prices utilized in the previous two sections. Following the methodology outlined in the next subsection, we construct a database that measures deviations from the law of one price. The variable of interest for analyzing deviations from the
the previous cross-section analysis, we estimate the sample over different 20-year growth spells.

Since the bilateral data on FDI flows that are necessary to build our instrument are only available from 1990, we test if the time variation of the FDI coefficient emerges also in the IV regressions by estimating the model separately for five 20-year periods: 1990-2009; 1992-2011; 1994-2011; 1996-2015 and 1998-2017. As the sample of countries for which we are able to compute the instrument is different from that of the OLS regressions described before, we show the IV results together with OLS results estimated over the same country sample.

In the baseline regressions, we use an exactly identified model in which net FDI inflows are instrumented with the value of _zit_ computed using the exogenous components of all FDI flows, regardless of their source (Table 4 ).

IV regressions suggest that FDI is positively associated with economic growth when we estimate the model over 1990-2009 and 1992-2011 (columns 2 and 4 of Table 4). However, the FDI

> 12Appendix Figure C.1 shows the share of North-South and South-South FDI received by developing and emerging countries over our period of analysis.

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30%. Moreover, we find that bond prices often recover relatively quickly during and after default spells, although the variation across episodes is also large. On average, creditors recoup their pre-crisis investment (measured one year before) within five years after the default; and in 25% of cases (upper quartile), investors recover their losses in less than one year. There are, of course, outlier episodes involving major upheavals such as wars, revolutions, or the break-up of empires (e.g., in Austria-Hungary, China, or Russia). However, in the majority of debt crises, investor losses are partial. Debt repudiation cases are comparatively rare.

On a more general level, our results reveal many parallels to the case of equity. As is the case for stocks, we find that sovereign external bonds show high excess returns coupled with a relatively low return volatility. The seminal work by Mehra and Prescott (1985) showed that standard asset pricing models are not able to reproduce the large empirically observed wedge between risky and riskless assets. Their contribution was followed by a stream of studies on the equity premium puzzle, largely focusing on the United States after World War II (WW2) (see Kocherlakota 1996; Campbell 2003). Compared to the literature on long-run equity returns, our analysis of external bonds covers far more countries, particularly encompassing emerging markets and developing countries. It also goes much further back.<sup>12</sup> There are, however, gaps in the bond pricing series of individual countries, and the market for external sovereign bonds shrinks in the Bretton Woods era of capital controls, and all but disappears during the syndicated bank lending spell of the 1970s and 1980s (our average country coverage is 70 years). There is also research on the “credit spread puzzle” for corporate bonds, typically using data from the past 30 years.<sup>13</sup> The high excess returns on external sovereign bonds have received much less attention
) _≤_ 1 and 0 _≤ HI_ ( _RIU_ ( _y_ ) _| y_ ) _≤_ 1, I have that 0 _._ 032 _≤ λ < ∞_ and 0 _._ 036 _≤ λ < ∞_ , , so assuming 0.04 shocks per quarter is within an admissible range in the model.<sup>74</sup>

The opportunity cost of leisure, _b_ , is set equal to 1. In Colombia there were no unemployment benefits in this period, so one must think about what the monetary compensation for the unemployed should be, relative to the average wage, or the average ‘replacement rate’. According to HKV2005, such a rate is 0.7 for European countries where benefits are relatively high, and 0.2

> 72Source: IMF, International Financial Statistics.

> 73 I use educational attainment as a proxy for worker types.

> 74 In ANV2009 _λ_ is set to 0.5 using one year as a unit of time, while in Hornstein, Krusell and Violante (2005)

> (hereafter HKV2005) _λ_ is set to 0.1 using one quarter as a unit of time.

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and 6.2% are publicly listed. The foreign ownership share is, on average, 10.7%, while the average government ownership is 0.7%. On average, firms are 17.5 years old.

Finally, we control for industry-level variation in the need for external finance. Specifically, we use the Rajan and Zingales (1998) indicator on the fraction of investment that cannot be financed through internal cash flows, computed over the 1980s for listed firms in the U.S. The underlying assumption in Rajan and Zingales and our work is that for technological reasons some industries depend more heavily on external finance than others and that this industry variation does not differ across countries. We use the self-reported industry categorization by firms in the Enterprise Surveys to match with the Rajan and Zingales classification. Since this variable is only available for manufacturing industries, we lose about a half of our sample. The average fraction of external need for finance across our sample is 0.29, varying from -0.45 (tobacco) to 1.14 (plastic products).

The correlations in Table 2 suggest that there is no systematic relationship between the country-level metrics of financial segment size. Not surprisingly, however, the average asset size of some of the institutional categories is positively and significantly correlated. The log of GDP per capita is, as expected, positively and significantly correlated with the mean asset size of all institutional categories except low-end NBFIs. There are no significant correlations between the asset shares of the different segments of the financial system and access to finance. There are, however, significant correlations between the average size of financial institutions and access to finance. Countries with larger banks have a higher share of firms with loans and overdraft and firms that complain less about financing obstacles. Countries with larger specialized lenders also have more firms with overdraft facilities or loans. Many of the firm characteristics are also correlated with each other. Countries with more small firms, for instance, have fewer listed and younger firms
- Chong, A., I. Cohen, E. Field, E. Nakasone, and M. Torero (2016, October). Iron deficiency and schooling attainment in peru. _American Economic Journal: Applied Economics 8_ (4), 222–55.

- Cunha, J. M. (2014). Testing paternalism: Cash versus in-kind transfers. _American Economic Journal: Applied Economics 6_ (2), 195–230.

- Dahl, G. B. and L. Lochner (2012, May). The impact of family income on child achievement: Evidence from the earned income tax credit. _American Economic Review 102_ (5), 1927–56.

- Dammert, A. C., J. de Hoop, E. Mvukiyehe, and F. C. Rosati (2018). Effects of public policy on child labor: Current knowledge, gaps, and implications for program design. _World Development 110_ (C), 104–123.

- De Giorgi, G. and M. Pellizzari (2014). Understanding social interactions: Evidence from the classroom. _The Economic Journal 124_ (579), 917–953.

- de Hoop, J. and F. C. Rosati (2014). Cash Transfers and Child Labor. _World Bank Research Observer 29_ (2), 202–234.

- De Hoop, J. J., J. Friedman, E. Kandpal, and F. C. Rosati (2017, September). Child schooling and child work in the presence of a partial education subsidy. Policy Research Working Paper Series 8182, The World Bank.

- De Hoyos, R. E., R. Estrada, and M. J. Vargas (2018, May). Predicting individual wellbeing through test scores : evidence from a national assessment in Mexico. Policy Research Working Paper Series 8459, The World Bank.

- Duflo, E., P. Dupas, and M. Kremer (2011a, August). Peer
-- Start of picture text --> Market share of current accounts by deposit level Market share of savings accounts by deposit level<br>100 27 15 16 17 18 20 100 113 93 105 107 13 18<br>80 80 10<br>21 20 18 17 16 12<br>60 20 60<br>40 40 86 88 85 ` 82 77<br>64 64 65 65 65 69<br>53<br>20 20<br>0 0<br><5 >5 & <10 >10 & <20 >20 & <50 >50 & < >100 <5 >5 & <10 >10 & <20 >20 & <50 >50 & < >100<br>100 100<br>Million COP Million COP<br>Private Domestic Banks Private Foreign Banks Public Banks Private Domestic Banks Private Foreign Banks Public Banks<br>Source: Own calculations based on Superintendencia Bancaria data<br>% Market share of current accounts % Market share of savings accounts<br><!-- End of picture text --> 24
as SOEs firms for which the main (top 1) shareholder is a government-related entity (following Ma et al., 2021). We merge our main dataset with 2007-20 firm-level data on firm ownership structure downloaded from Wind. We consider SOEs to be all firms with a government-related principal shareholder any year between 2007 and 2020. Around 37 percent of firms in our domestic listed sample are SOEs. They are about twice as large as the rest of the (private) firms.

> 28 As two additional robustness tests, we use the log of equity raised as dependent variable (instead of the amount raised over assets) and exclude financial firms (right columns in Table 7). The log of equity raised as dependent variable provides an alternative equity issuance measure that is not scaled by firms’ assets. Financial firms only constitute around 3.4 percent of our sample and excluding them barely changes the results.

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Finally, the Treasury could pressure dealers to carry all its products. From a logistical standpoint, the Treasury could argue that it has provided efficient and cost-effective securities custody and delivery facilities. In exchange, dealers should demonstrate their ability to attract investors for different sections of the Treasury’s maturity spectrum.

_Zero investment cost._ Aside from contributing connectivity to the Registry of Scripless Securities, the Treasury did not have to make any hard investments to acquire an e-business platform comparable with private offerings. Smetrix took the entrepreneurial risk in building the platform and partnered with the Data Center to provide it to the Treasury.

_Ability to offer all retail government securities._ The Expanded Small Investors Program provides a platform for the Treasury to offer all retail government security products. The Retail Treasury Bond program is currently offered to retail investors through firm underwriting. By offering the bonds through the program on a similar noncompetitive basis, the Treasury could generate savings by eliminating underwriting fees.

_Investor education._ Philippine regulators have had a hard time suppressing financial scams. The Expanded Small Investors Program provides an opportunity for the Treasury to expose new or less sophisticated investors to such essential issues as market risk and differences between bank deposit products and fixed income securities and between registry and book-entry recording of ownership, as well as to increase investor expectations in terms of risk and reward propositions **.** _Increased investor expectations for service and convenience._ The real-time nature of the Expanded Small Investors Program and the provision of transactions and information over the Internet will give investors new levels of convenience and service. Until now government investment services in the Philippines have been unable to match the convenience of private services.

_Expanded savings mobilization._ The 1998 launch of the Small Investors Program made the Treasury aware of the program’s ability to attract participants even among those without bank services. The expanded program will offer a product for retail investment that directly competes with other investment products, such as deposits and mutual funds. And given the program’s better rates, it