rafmacalaba/data-use-mentions-extended huggingface dataset:
that the formal rule of law and institutional constraints on government are not always necessary for economic growth in a developing or transitional economy. In particularly, using a crosscountry panel data, Fan et al. (2009) find that FDI per capita is not robustly related to the rule of law once the analysis controls for a country‟s economic track record and its volatility. Their similar findings based on cross-country panel data that are completely different from our withincountry, cross-sectional regional data add to our confidence about the key results in the current paper.

# **References**

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- Blonigen, B. A. (2005). „A review of the empirical literature on FDI determinants‟, Atlantic Economic Journal, 33, pp. 383-403.

- Bull, C. (1987). „The existence of self-enforcing implicit contracts‟, Quarterly Journal of Economics, 102, pp. 147-59.

- Cai, H., Fang H., and Xu, L. C. (forthcoming). „Eat, drink, firms and government: an investigation of corruption from entertainment expenditures of Chinese firms‟,  Journal of Law and Economics.

- Chen, Q
668|
|Total organized share|0.006|0.008|0.006|0.006|0.332|
|B. Employment weighted distribution||||||
|Unorganized tiny (1-9 employees)|0.731|0.593|0.649|0.618|0.040|
|Unorganized micro (10-19 employees)|0.076|0.142|0.126|0.128|0.046|
|Unorganized small (20+ employees)|0.003|0.054|0.053|0.061||
|Organized tiny (1-9 employees)|0.002|0.003|0.003|0.003||
|Organized micro (10-19 employees)|0.010|0.011|0.011|0.011||
|Organized small (20-39 employees)|0.019|0.018|0.014|0.015|0.074|
|Organized medium (40-99 employees)|0.029|0.037|0.025|0.029|0.148|
|Organized large (100-499 employees)|0.049|0.061|0.054|0.071|0.366|
|Organized mega (500+ employees)|0.081|0.081|0.064|0.064|0.326|
|Total unorganized share|0.810|0.789|0.828|0.807|0.086|
|Total organized share|0.190|0.211|0.172|0.193|0.914|

Notes: Indian descriptive statistics taken from Annual Survey of Industries and National Sample Statistics. U.S. descriptive statistics taken from 1997 Census of Manufacturers. Unorganized/organized shares for United States use establishment sizes to mimic Indian definitions.
, 2008). However, such programs remain controversial. This is particularly true of programs geared to low-skilled migrants, such as seasonal migration programs, as witnessed by the policy debate in the United States over a new guest worker program and continued debate in Western Europe about the role of seasonal workers. Some critics of such programs raise concerns that workers will over-stay and/or compete down the wages of native poorer workers (e.g. Borjas, 2007), while others raise concerns about the possible exploitation of workers and whether workers can earn enough to make it worthwhile if the duration of work is short.<sup>2</sup> Lacking from this debate is credible evidence as to what the development impact is of international seasonal worker programs. The few existing studies are based on ex-post surveys of migrants, and lack credible counterfactuals of what would have happened to households in the

> 1 Quoted in “Seasonal work policy benefits Pacific says Peters”, _Islands Business_ , October 26, 2006. <u>http://www.islandsbusiness.com/news/index_dynamic/containerNameToReplace=MiddleMiddle/focusModuleID=1 30/focusContentID=6691/tableName=mediaRelease/overideSkinName=newsArticle-full.tpl</u> (accessed August 11, 2010).

> 2 These concerns are discussed in Ruhs (2006), Pritchett (2006) and OECD (2008) among others.

2
summarize the data underlying the panel estimators employed later and offer further insight into the nature of the sectors. First, as has been noted in other developing countries, there is a relatively high degree of mobility. For instance, of those declaring themselves formal salaried at the beginning of the period, only 63% were still in that sector at the end of the year. Second, to the degree that turnover is a measure of attachment to a sector (as opposed to rates of firing), formal salaried, civil employment and self-employment show a comparatively high percentage of stayers, (low rate of turnover) at 63%, 69%, and 66% respectively. Informal salaried employment, on the other hand, has the highest rate of turnover; the proportion of stayers is only 45% implying that over half of the sector leaves to other sectors in a year. This, and the demographic patterns noted above, are consistent with it being a sector of entry of relatively young people who are shopping around for their next (superior) employment. Further insights can be gleaned from studying the patterns of mobilility among sectors although, as with the conditional wage comparisons discussed earlier, they cannot offer robust conclusions about the relative desireability of the various sectors.<sup>14</sup> Hence, we turn to an examination of the job satisfaction data. Returning to the unconditional tabulations in Table 1, several notable facts emerge. To start with, relative to other regions, Ghanaian workers are somewhat less satisfied with their jobs. Using the more homogeneous group of formal salaried workers as the comparator, Ghana yields a value of 3.33. To put this into perspective, consider that a rudimentary rescaling of the seven point scale used by Benz and Frey (2008b) into a comparable five point scale yields

> 14For instance, consistent with the age patterns discussed above, informal salaried workers have relatively high rates of transition to formal employment (15%) destination sector, and to self-employment (22%)
|0,000|0,000|0,700|0,000|0,000|0,484|0,000|0,000|0,248|
|Womenproportion*|0,007|0,007|0,287|-0,002|0,005|0,670|0,002|0,005|0,660|40,014|0,004|0,001|
|Constant|0,646|0,188|0,001|-1,513|0,129|0,000|-1,152|0,121|0,000|-2,860|0,131|0,000|

Source: Based on "Pesquisa Nacional por Amnostra de Domicilios" (PNAD) ofthe 1976 and 1996.

Note: * excluding the head.
<!-- Start of picture text --> under 0.2<br>0.2 − 0.4<br>0.4 − 0.6<br>0.6 − 0.8<br>over 0.8<br><!-- End of picture text --> Figure 7: This map shows the Ethnic Linguistic Fractionalization (ELF) index across Sierra Leone’s Census Enumeration Areas. As the map illustrates, the level of fractionalization outside of the Western Peninsula is quite low. Seventy-percent of the NPS’ respondents identify as a member of the dominant ethnic group in their ward.

<!-- Start of picture text --> under 20 under 20<br>20 − 40 20 − 40<br>40 − 60 40 − 60<br>60 − 80 60 − 80<br>over 80 over 80<br>(a) Support for the APC (b) Support for the Opposition<br><!-- End of picture text --> Figure 8: These maps show the average percentage of respondents by chiefdom who voted for the APC and the opposition in the 2007 national elections, according to the 2008 NPS survey.

36
However, when -- like in our case -- one is also interested in the standard errors of the parameter estimates, as well as in the variance components themselves, maximum likelihood estimation offers the best performance, especially if the sample is severely unbalanced.<sup>13</sup>

# _II.3 Data_

We implement the empirical approach described above using the Dollar and Kraay (2002) dataset, which comprises 794 country-year observations for which both the Gini coefficient and the quintile shares are available.<sup>14</sup> The dataset combines observations for which both the Gini coefficient and the quintile shares refer to gross (i.e. before taxes and transfers) income (47 percent of the observations); net (i.e. after taxes and transfers) income (29 percent of the observations); and expenditure (24 percent).

Table 1 presents some descriptive statistics. The average Gini coefficient is roughly the same in the income and expenditure subsamples -- 0.37 for income and 0.38 for expenditure. This is somewhat surprising since on the basis of conventional

> 11 These assumptions can be further relaxed to allow for heteroskedasticity of

_it_ ε . _j_

> 12 See Baltagi _et al_ . (2001) and Davis (2002) for discussion.

> 13 See Rabe-Hesketh _et al._ (2004) on the computational aspects of ML estimation in this context.

> 14 We discard the 158 extra observations for which Dollar and Kraay construct the quintile shares from the Gini coefficient using equations (1)-(3), and thus assuming that the distribution of income is lognormal -- which is precisely what our regressions aim to test.

-7-
the inverse of the iteration sequence number raised to a power that varies in increments of 0.1 between 0 and 2.0. The second is the number of iterations, which varies from 1 to 20. Our grid search yields best fits for decay and iteration parameters of 1.0 and 10, respectively.

Using these parameters, we incorporate wind displacement effects as follows. For each year and month, we use our industrial and fire emissions data to compute total CO2 emissions separately for industry and fires in each grid cell. We route these emissions across nearby cells through 10 sequential iterations, identifying the destination cells by iteration. Once this process is complete for all cells in the grid, we proceed cell-by-cell. For each cell, we add across observations for displaced CO2 from every other cell, with separate totals by iteration step. We weight these totals for industry and fire CO2 by the inverse iteration step number (which incorporates the decay function). Next, we add across the weighted totals to obtain the overall decay-weighted totals for wind-displaced CO2 in each cell. These are the variables _DI_ and _DF_ in the econometric model (equation [1]).

> 6 We use the IHST rather than the logarithmic transformation because most of the observations in the data set are zeros (see Burbidge, Magee and Robb (1988) and Layton (2001)).

> 7 The bearing calculation formula can be viewed at https://www.movable-type.co.uk/scripts/latlong.html.

6
recall diary preface read out to respondents suggested secondary activities that might include collecting water or cooking, alongside caring for children. This yields different approaches to capturing simultaneous activities — while the smartphone diary did not distinguish between main and secondary activities (every activity was selected on its own, without any limits on the number of simultaneous activities that can be recorded), the recall diary did distinguish between the two, and encouraged respondents to consider a specific secondary activity that might have typically been done alongside the main one. As a result, close to 10 percent of respondents in the smartphone treatment arm often reported three or more activities (although typically not more than three) within a 15-minute or shorter duration, compared to the maximum ceiling of two activities in the recall diary.

The analysis shows that nearly all (around 95 percent, for both treatment arms) of women’s daily multitasked non-leisure time was from conducting different unpaid domestic and care activities together. However, if we consider leisure activities (see Appendix Table A1 for the breakdown of leisure activities), the share of women’s multitasked time in unpaid work was greater in the smartphone arm (38 percent, compared to 23 percent in the recall arm). As discussed below, this stems from greater reporting in the recall arm of multitasked time in leisure; the smartphone arm, on the other hand, revealed higher participation in multitasked employment, unpaid work, and transport activity.

To provide a richer understanding of different types of activities that were conducted together in both treatment arms, Tables 10 and 11 present heat map charts for the share of women and men, respectively, 24
6) accounting for sector, year, and country group fixed effects. The fixed-effects estimation technique is widely use because it yields consistent estimates without strong structural assumptions (Head and Mayer, 2013). Equations (4) to (6) are therefore estimated focusing on the effects of skills, migration, human capital endowment on GVC participation. As discussed previously, skilled labor data are derived from the GTAP IO tables and skill mobility is proxied by net migration-to-population ratio to analyze the impact of foreign labor contribution on GVC activities. For comparative purpose, we independently estimate equations (4) to (6) for SSA countries and for the rest of the world. This is done to assess if the effects of skills and migration on GVC participation in SSA are any different from what is observed in other parts of the world. To the best of our knowledge, this study is the first to assess the impacts of skills, migration, human capital endowment on the integration of SSA countries in backward and forward GVCs.

16
63 Minneapolis: University of Minnesota Press, 1987, pp. 26-47.

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- Jappelli, Tullio and Pagano, Marco, "Saving, Growth, and Liquidity Constraints," Quarterly Journal of Economics, February, 1994, 109(1), pp. 83-109.

- Jaramillo, Fidel, Schiantarelli, Fabio and Weiss, Andrew. "Capital Market Imperfections, Financial Constraints and Investment: Econometric Evidence from Panel Data for Ecuador," Journal of Development Economics, 1996, forthcoming.

- Jayaratne, Jith and Strahan, Philip E. "The Finance-Growth nexus: Evidence from Bank Branch Deregulation," Federal Reserve Bank of New York Research Paper No. 9513, 1995.

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Jevons, W. Stanley. Money and the Mechanism of Exchange, London: Appleton, 1875.

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-
and graduation. A central piece of the model, student effort, has a direct effect on the completion of classes and an indirect effect mitigating risks on class completion or college persistence. We have estimated the model using rich administrative data from Colombia. According to our estimates, effort has a much greater impact than ability on class completion. Failing to model effort as an input to class completion leads to overestimating the role of ability by two or three times, and to favoring policies that promote positive selection of new students instead of effort. We have used our parameter estimates to simulate multiple free college programs. According to our simulations, universal free college expands enrollment the most but has the highest per-graduate cost and does not raise graduation rates. Performance-based free college, in contrast, delivers a slightly lower enrollment expansion but has a greater graduation rate and a lower per-graduate cost. Performance-based free college faces students with greater risks than the current baseline or universal free college; precisely for this reason it elicits greater

> 30Notice that the initial share of 27 percent is higher than the initial fraction of high school graduates that finish college, equal to 14.5 in the baseline. The reason is that 27 percent includes graduates from all bachelor’s programs (rather than only five-year programs) as well as graduates from two-year programs. This is because the college premium is calculated for all higher education graduates, based on data that does not distinguish between graduates from bachelor’s and two-year programs.

> 31We use the point estimates of 1.4 from Katz and Murphy (1992) and Heckman et al (1998), 2.5 from Card and Lemieux (2001), and include lower value of 1.2. For each _ω_ value, the intercept has been adjusted to generate the same college premium for the year 2012.

> 32These results are consistent with Garriga and Keightley (2007), who conduct a similar analysis for the U.S. in a model that endogenizes the college premium, government budget constraint,
45

- National household expenditure surveys are useful because they enable identification of the poor. They are less useful for calculating access to electricity. Agreeing how to standardize analysis across divergent household surveys among energy practitioners would help compare computation of access rates across studies.

- More systematic collection of freely acquired basic goods and services to separate cash expenditures from own consumption would help estimate disposable cash income, which is needed to assess the ability to pay for electricity.

- A national household expenditure survey cannot substitute a dedicated energy survey. One problem with energy surveys is that information on total household expenditures is not collected because that requires a long list of questions. One option is to launch the energy survey in parallel with the national household expenditure survey, visiting the same households. Further, examination of household survey data side by side with data on residential customers from utilities would enrich analysis considerably.

This paper has examined access largely from the point of view of demand. But supply constraints are equally important. Indeed, where data on community access and household connection to the grid were available, most unconnected households did not live in electrified communities, a result dominated by lack of community access in rural areas. This points to the importance of developing a financially viable strategy for rural electrification, while making grid electricity affordable in urban areas.
Given the favorable loan characteristics, the positive and significant demand for the new loan product is only a necessary and not a sufficient condition for the intervention to be effective in improving sanitation.<sup>40</sup> In addition to potentially diverting the sanitation loan for other investment purposes (whose financing product might be more expensive), households might also simply shift their financing source for sanitation itself, implying that even if the loans were used for sanitation, they were not used for toilets that would otherwise not have been constructed. It is therefore possible that the sanitation loan uptake might not translate into new toilets. Thus, we next turn to considering the effects of the intervention on toilet uptake.

# **6.2 Sanitation investments**

The sanitation loan could be used for two types of sanitation investments: (i) construction of a new toilet, or (ii) upgrade or repair of existing toilets. As shown in Table 4, which tabulates responses from clients who took a sanitation loan (as reported in the MFI administrative data) on what they used it for, a majority of clients (73 percent) report using the sanitation loan for the construction of a new toilet. Less than 5 percent report using the loan to upgrade (3 percent) or repair (1 percent) a toilet. A small number of clients report using the loan for sanitation and other purposes. Even if we assume that these clients intended to upgrade or repair an existing toilet, at most 11 percent of clients who took a sanitation loan used it to upgrade or repair a toilet. Thus, the primary _reported_ reason for taking a sanitation loan was to construct a _new_ toilet.

Table 4: Reported loan use

||New toilet|Upgrade|Repair|Other only|Sanitation &<br>other|Total|
|---|---|---|---|---|---|---|
|SL|146<br
# **1. Introduction**

Accurate estimates of men’s and women’s employment are at the heart of understanding sources of productivity and economic growth and designing well-targeted, gender-sensitive labor policies. Country employment surveys, spanning labor force surveys and labor modules in multi-topic household surveys, are usually structured to ask working-age individuals to report the incidence of and time allocation to a range of employment-related activities over different reference periods, for example over the last week or 12 months. The common “business-as-usual” approach in these surveys, however, can involve interviewing respondents in group settings; proxy respondents reporting on behalf of individuals that are not available for interviews; and other issues affected by survey time constraints, including lack of follow-up questions linked to difficult-to-measure or seasonal activities, as well as intra-household roles in enterprises. All of these variations can potentially create errors in reporting employment, particularly when questions involve longer recall periods, or for types of employment that are more difficult to measure, including seasonal/informal work. A key question, as a result, is whether individual interviews with respondents — focusing on self-reporting and one-on-one (as opposed to group) settings — have a significant effect on reporting of employment over the standard practice.

This study aims to answer this question by leveraging two national surveys that were implemented concurrently by the Malawi National Statistical Office with different approaches to respondent selection in collecting individual-disaggregated survey data, including on employment — and that allow us to compare the data obtained under the business-as-usual approach (the Fourth Integrated Household Survey (IHS4) 2016/17) versus individual interviews that are conducted in private (the Integrated Household Panel Survey (IHPS) 2016). As compared to individual interviews conducted in the IHPS, our findings show that the business-as-usual approach leads to significant underreporting of employment in livestock-related activities and household non-farm enterprises (in management and worker capacity) – with stronger effects for women and under a recall period of 12 months, as opposed to 7 days. The analysis also reveals underreporting in wage employment among