rafmacalaba/data-use-mentions-extended huggingface dataset:
C, column 3).<sup>8</sup> In total, the cash transfer group averaged MK 5,524 more cash on hand on the day of the transfer, and MK 3,737 more one week later. The savings default treatment shifted assets to formal bank accounts and, as we show in the next section, away from other types of savings. This evidence of a positive effect of the savings defaults on bank savings motivates the examination of the composition of expenditures in the next subsection.

# **5.2 Household survey outcomes**

Data from the household survey confirm that the savings default treatment shifted funds towards NBS bank accounts and away from other types of saving. We follow the structure of our survey instrument (adapted from Malawi IHS-3) in categorizing savings as formal financial savings (accounts at NBS or other banks), informal savings (village savings groups,

> 7Reporting net deposits rather than the level of bank balances is a limitation of the administrative data we were able to obtain from NBS.

> 8While the focus is on assessing the impact of default savings, we note that recipients of the large transfer compared to the control group saved a significant portion of the transfer in the bank for more than two weeks and that higher net deposits (relative to the control group) persist for 90 days after the initial transfer (result not shown).

11
766|2.712|3.630|
|Slope over lowest tercile of DB|0.616|0.422|1.228|0.119|0.743|-0.005|
|(t-stat)|1.179|1.732|1.849|0.482|0.640|-0.012|
|Slope over middle tercile of DB|0.287|0.074|0.010|0.195|-0.210|-0.015|
|data(t-stat)|0.371|0.204|0.010|0.524|-0.118|-0.024|
|Slope over upper tercile of DB|0.126|0.012|-0.018|-0.027|0.105|0.036|
|data(t-stat)|0.289|0.059|-0.029|-0.119|0.121|0.116|
|N|88|88|72|72|87|87|
|R2|0.088|0.081|0.076|0.055|0.011|0.004|
|F-test of spline terms|0.545|0.203|0.166|0.435|0.855|0.963|
|Outliers deleted|Yes|Yes|Yes|Yes|Yes|Yes|

# **VI. Comparing changes in Doing Business with changes in ES**

The results shown so far are based on cross-national comparisons in which we have matched the DB indicator to the year of the ES survey. DB has been updated annually since its introduction in 2003. However, the ES have been repeated in only a few countries, generally with a 3-5 year lag. This section uses only those countries for which an ES was fielded, there was then a formal
Measuring True Sales and Underreporting with Matched Firm-Level Survey and Tax office Data There remains, however, the important issue of whether the direct approach provides reliable information, even if only about average underreporting behavior. It has been noted that the direct approach may provide a lower-bound estimate of actual underreporting (Schneider and Enste 2000, 92). The direct approach relies on the untested assumption that firms report truthfully about untruthful reporting, but this may not hold in practice. Therefore in the next section we develop an alternative approach which allows for (systematic and nonsystematic) misreporting in the survey and which estimates underreporting at the firm-level.

# **3 A MIMIC model**

Our approach is to derive a MIMIC model for the estimation of the true sales of a firm taking into account firm-level incentives to comply with taxes and a production function technology linking true sales with observable firm-level production characteristics. Generally, a MIMIC model is a structural equation model with latent variable(s) ( ) for which multiple indicators ( ) and multiple causes exist (X). Apart from the shadow economy literature mentioned in the introduction, the MIMIC model has also been applied to estimate the demand for health care (Van de Ven and Van der Graag 1982) and manufacturing productivity growth (Siegel 1997). The standard MIMIC model consists of both structural equation(s) (eq. 1) and measurement equation(s) (eq. 2): 11
panel; jurisdictions are time periods within a single country where there have been changes in local government participation in financing road works--the case of Korea; and jurisdictions are state and local governments within a single country--the case of Germany.

The cross-country panel is taken from the International Road Federation (IRF)<sup>2</sup> 1 Statistics, which provide yearly an extraordinarily rich set of information on roads disaggregated by level of government. We are able to distinguish between central and local government expenditures, where the latter encompasses all levels of government (local and regional governments) other than the central government. From this data set, it has been possible to develop a continuos measure of decentralization disaggregated by level and type of road activity. Additional information includes data on costs also by level and type of activity and the condition of the network. The panels are not balanced because some of the observations are missing. We arrive at a total of 262 observations for measuring the effect of different levels of decentralization on resource and preference costs.

A cross-country panel was selected because it has pre- and post- decentralization data for a variety of countries which decentralized or centralized over time (e.g., Korea, Indonesia, and Colombia) as well as countries which did not change their levels of decentralization over the period of analysis (e.g., Switzerland, Germany, and Tanzania). The pre-decentralization data serves as a control for the post-decentralization data so that the impact of decentralization as a continuous variable can be estimated. This data set is employed to verify the validity of the double-cost hidden level of effort approach to measuring the impact of decentralization on performance. With the country level panel we determine whether there are optimal levels of decentralization for provision of roads and estimate empirically the impact of decentralization on road performance. Table 1 displays the information contained in the cross-country data set.

The data set for Korea is also derived from the IRF source although the analysis is longitudinal and covers a
by credit card) as well as goods and services obtained via nonmonetary means. The latter includes donations (presenting in-kind transfers), production for household self-consumption, and other sources such as withdrawal from business or trade where no money was involved.

The consumption aggregate is composed of the following components:

- 1) _Food consumption._ We include the value of food consumed from all possible sources, as measured in POF. This includes food acquired for consumption at home, which is collected in the household questionnaire of frequent acquisitions (POF 3). Food consumed at home can be acquired via monetary means, obtained through own production, or received in kind or via other means that do not involve monetary payment. The value of consumption of FAFH is collected in the individual-level expenditure questionnaire on nonhousehold goods and services (POF 4). Again, this component of food consumption might have been acquired via monetary as well as nonmonetary means. We aggregate the values of individual consumption of FAFH at the household level and include it in the consumption aggregate. Finally, POF also collects information on food consumption outside the home – in particular, meals consumed in settings like at school or on vacation. This information is collected outside of these two questionnaires, since it is collected in expenditure modules on education and vacation expenses, for instance. Following Deaton and Zaidi (2002), with the exception of school meals obtained via nonmonetary means, we include the value of this type of food consumption in the consumption aggregate.<sup>10</sup>

- 2) _Consumption of nonfood items._ For the value of nonfood consumption to be included in the consumption aggregate, we need to make a few choices in order to make the aggregate adequate for our purpose of analysis. POF collects information on a wide range of nonfood items, but several are typically not included in the construction of a consumption aggregate used for welfare analysis. Examples include taxes or “lumpy” acquisitions that are usually made at a low frequency (see Deaton
baseline equation regresses the mid-point growth rate of exports at the firm-destinationproduct-year level, which we used for the export growth decomposition of Table 6, on measures that track developments in foreign demand, firm characteristics, and changes in a number of measures of export costs over the period 2002-2010. The regression is carried out by means of ordinary least squares (OLS).

Our dependent variable, the mid-point growth rate of firm i exports is constructed as in Bricongne et al, 2011, to which the reader is referred for a definition. It has three dimensions: year t, 8-digit HS product k, and destination c. It is computed from export flows in Pakistan’s Rupees. We observe the export performance of all firms that exported at least once over the period of reference. This is possible because the mid-point growth rate allows computing rates also for entries and exits. We explain the change in exports with the following variables.

41
# **Figure 4 Sri Lanka Official and Unofficial Remittances (US$ Million)**

<!-- Start of picture text --> Figure 4.4 Sri Lanka. Official and Unofficial<br>Remittances (US$ millions)<br>1000<br>800<br>600<br>400<br>200<br>0<br>1985 1990 1995<br>Official Unofficial<br><!-- End of picture text --> _Source: World Bank (2005a)_ _In addition to cost and speed, informal remittance systems also fare more favorably for migrants, with respect to the formalities required to transfer money, reliability, and convenience._ The informality of _Hawala_ makes it attractive to many Sri Lankan migrants who find banks and other financial institutions uncomfortable to deal with. The lack of bureaucracy renders informal services accessible to less educated customers, many of whom live in rural areas where alternatives are not available in any case. Informal systems are also reliable. Trust and the cultural importance of one’s reputation and good name perform an effective self-regulatory function. Disputes and errors are settled among informal service providers who assume the risk of a counterpart’s default or law-enforcement actions.

_The convenience of door-to-door service is appealing to all customers, especially in the regions where transportation is poor and to female migrants in remote and traditional regions, where they may not be allowed to leave the house._ In some instances, as field surveys indicate, informal service providers visit the workplaces of expatriates to collect money for remittances. Private banks have opened branches in migrant-destination countries to assist Sri Lankan nationals remitting their earnings, and these branch offices have managed to attract a number of clients through personalized service. However, due to the constraints of work conditions, housemaids still prefer to use informal channels to remit their earnings. With the fluctuation of the dollar, many of these women are unaware that their informal contacts do not give them a fair exchange rate and
**Figure 5: Inequality earnings (Gini) by age group and gender: 2000, 2007 and 2014. Restricted to workers with college.**

<!-- Start of picture text --> A. Males B. Females<br>23-30 31-40 41-50 51+ 23-30 31-40 41-50 51+<br>.4 .4<br>.3 .3<br>Gini .2 Gini .2<br>.1 .1<br>0 0<br>2000 2007 2014 2000 2007 2014 2000 2007 2014 2000 2007 2014 2000 2007 2014 2000 2007 2014 2000 2007 2014 2000 2007 2014<br><!-- End of picture text --> Notes: Authors’ calculations using quarterly Labor Force Surveys from 2000 to 2014. Earnings are in constant Mexican Pesos 2014:1. Earnings refer to full-time workers (at least 30 weekly hours of work) with a valid wage. Includes workers with college education: salaried, self-employment and owners. Earnings below and above the 1 and 99 percentile (within gender and education group) are dropped. Lines are smoothed by a moving average with a 0.4 weight to the current observation and 0.3 to the previous and post observation.

In order to analyze the roles of the degraded tertiary and skill-obsolescence hypotheses, we calculate earnings over time and by cohort. This calculation is important because it depicts how wages have changed over time for the same type of workers.<sup>8</sup> The degraded tertiary hypothesis should show that wages for recent cohorts declined more pronouncedly (due to increased competition for the same jobs and that the quality of those workers is inferior to that of previous graduates). The skill-obsolescence hypothesis shows that older cohorts experienced a more pronounced decline in their wages over time.

**Table 3: Mean Log Hourly Wage by Cohort. Males with college education.**

|<br>Cohort|<br>2000|<br>2002|<br
Komives, Whittington, and Wu "Infrastructure Coverage and the Poor: A Global Perspective" urban areas now have electricity service. The relationship between income and coverage is remarkably similar for electricity, in-house water connections, and sewer. As monthly household incomes increase from US$100 to US$250, coverage of all these infrastructure services rises rapidly. As expected, coverage is much higher in urban than in rural areas for electricity, water, sewer, and telephone service.

The findings confirm that the very poor rarely have these infrastructure services. There are, however, exceptions. The very poor often do have electricity if they live in urban areas. The very poor in Eastern Europe and Central Asia have much higher levels of coverage than elsewhere in the world; they often have electricity, water, sewer, and telephone services. The results also suggest that if the poor have access to services in their communities, many will in fact decide to connect.<sup>7</sup> Where the very poor do not have formal infrastructure services, informal, private, and community infrastructure solutions fill the gap for many households. Few households in any of the fifteen countries in our sample report using unimproved water sources or candles for lighting. However, many households at all income levels and in both rural and urban areas used wood, thatch, or dung for cooking fuel. Few poor households without private telephones have public telephones in their communities, and the vast majority of the poorest rural households have no toilet, sewer, or septic facilities in their homes.

# 2. **The data: Livings Standard Measurement Study Surveys in fifteen countries**

The World Bank initiated the LSMS program in the 1980s to improve the quality of survey data available for policy research and analysis in developing countries. Since then more than twenty countries have administered nationally-representative household surveys based on the LSMS model of questionnaire design and quality control. The multi-country data set used in this analysis is cornposed 7In this paper, we reserve the term
Accessibility to economic opportunities is widely regarded as an indicator of the ability of transport and land-use in cities to connect residents with its opportunities (Nakamura & Avner, 2021). Most studies measuring access to opportunities, however, focus only on travel time (El-Geneidy et al., 2016; Foth et al., 2013; Levinson, 2013; Peralta-Quiros et al., 2019; Wu et al., 2021). While travel time is an important factor that impacts travel decisions and limits accessibility, there are many other elements that affect people’s travel behavior (Cui & Levinson, 2018), including the monetary cost of travel. Recent studies have started to incorporate monetary costs in accessibility analyses (Bittencourt & Giannotti, 2021; Conway & Stewart, 2019; Herszenhut et al., 2022; Oviedo et al., 2019), however they have focused on understanding existing relationships between travel times, travel costs, and other socio-economic factors, rather than assessing the impact of a policy mechanism.

In this paper, we quantify the impacts of a carbon price induced increase in fuel prices on transit services through a study on changes in access to employment opportunities and inequality in two cities: Kinshasa, Democratic Republic of Congo, and Rio de Janeiro, Brazil, leveraging General Transit Feed Specification (GTFS) data and socio-economic data. The aim is first to understand the magnitude of the impacts of an increase in transit fares on accessibility to jobs in both cities in aggregate, by income group and location; and, second to provide information to support the development of more targeted and nuanced policies that can offset negative distributional effects of carbon pricing policies on transit accessibility. The paper addresses four main research questions:

1. How do carbon price induced fuel price increases affect employment accessibility in aggregate?

2. Are any specific neighborhoods or socio-economic groups more severely affected?

3. In the absence of complementary measures, do carbon pricing policies further exacerbate existing inequalities?

4. Do carbon pricing policies risk further excluding some groups
Table C.15: National Estimates of Effect of Schooling on Beliefs Regarding Women’s Empowerment, Married Women Only

||Travel to Visit<br>Family / Friends<br>(1)|Personal<br>Healthcare<br>(2)|Large Household<br>Purchases<br>(3)|
|---|---|---|---|
||A. Wife should|at least have a|say in decision|
|�<br>Years of Schoolingizy|-0.056|-0.066|-0.065|
||(0.043)|(0.040)|(0.035)|
||[0.194]|[0.097]|[0.066]|
|Mean of Dependent<br>(Pre-Reform Cohorts)|0.783|0.721|0.650|
|First Stage F-Statistic|6.60|6.59|6.59|
|N|18,138|18,139|18,139|
||B. Wife should|be able to make|decision alone|
|�<br>Years of Schoolingizy|-0.064|-0.029|-0.041|
||(0.039)|(0.030)|(0.027)|
||[0.102]|[0.334]|[0.118]|
|Mean of Dependent Variable<br>(Pre-Reform Cohorts)|0.163|0.161|0.128|
|First Stage F-Statistic|6.60|6.59|6.59|
|N|18,138|18,139|18,139|

_Source_ : Author’s analysis based on data from the Ethiopian Demographic and Health Survey (in years 2005, 2011, and 2016). _Note_ : The
By contrast, negotiated land reform in South Africa has been adopted in the context of the national reconstruction program, in an environment in which productive small-scale agriculture was eradicated almost a century ago. This implies that, in its present form, the program bears many similarities to an urban settlement project and greater effort is required to establish the decentralized infrastructure necessary to implement land reform, to provide complementary services such as marketing and technical assistance, and to increase beneficiaries' agricultural and entrepreneurial capacity.

# 4.1 BRAZIL

With a land distribution among the most unequal in the world, Brazil's situation is similar to Colombia's in a number of respects. There is a very large and vocal political demand for land reform; a recent FAO study estimates the number of families who are potential candidates for land reform at 2.5 million. A land reform institute (INCRA) was established in 1969, distributing 10 million hectares to 200,000 families and colonizing about 14 million hectares for about 75,000 beneficiary families since then. Land reform has recently acquired considerable political importance; a federal Minister for Agrarian Reform was appointed in 1996 and the land reform budget tripled from US$0.4 billion in 1994 to $1.3 billion in 1995 with a further increase to $2.6 billion proposed in 1997.

The large majority of these federal funds will be spent according to the oldprocess which has been costly (about $30,000 per beneficiary) and bureaucratically cumbersome. However, state governments in the Northeast have been moving ahead and set up a decentralized market assisted pilot scheme. 32 This scheme (supported by a 90 million $ external loan) aims to speed up the land reform process, reduce costs, and provide the basis for a model that could eventually be adopted nation-wide.<sup>33</sup> The main differences from the old mechanism are the following (compare table 1):

- (i) Rather than relying on a lengthy process of expropriation, land is
- Davis, Lucas W. and Paul J. Gertler (2015). “Contribution of air conditioning adoption to future energy use under global warming”. _Proceedings of the National Academy of Sciences_ 112, 5962–5967.

- De Haas, Ralph et al. (2021). _Managerial and Financial Barriers to the Net-Zero Transition_ . SSRN Scholarly Paper. Rochester, NY.

- Dechezlepr être, Antoine et al. (2011). “Invention and Transfer of Climate ChangeâMitigation Technologies: A Global Analysis”. _Review of Environmental Economics and Policy_ 5. Publisher: The University of Chicago Press, 109–130.

- Dechezleprêtre, Antoine, Matthieu Glachant, and Yann Ménière (2008). “The Clean Development Mechanism and the international diffusion of technologies: An empirical study”. _Energy Policy_ 36, 1273–1283.

- (2013). “What Drives the International Transfer of Climate Change Mitigation Technologies? Empirical Evidence from Patent Data”. _Environmental and Resource Economics_ 54, 161–178.

- Dessaint, Olivier and Adrien Matray (2017). “Do managers overreact to salient risks? Evidence from hurricane strikes”. _Journal of Financial Economics_ 126, 97–121.

- Dillender, Marcus (2021). “Climate Change and Occupational Health: Are There Limits to Our Ability to Adapt?” _Journal of Human Resources_ 56. Publisher: University of Wisconsin Press Section: Articles, 184–224.

- Downey, Mitch, Nelson Lind, and Jeffrey G. Shrader (2023). “Adjusting to Rain Before It Falls”. _Management Science_ .

- Duflo, Esther et al. (2013). “Truth-telling by Third-party Auditors and the Response of Polluting Firms: Experimental Evidence from India*”. _The Quarterly Journal of Economics_ 128, 1499–1545.

- Dunne, John P., Ronald J. Stouffer, and Jasmin G. John (2013). “Reductions in labour capacity from heat stress under climate warming”. _Nature Climate Change_ 3, 563–566
**Table 4: Use of first difference in the logarithm of the unemployment rate**

||(1)<br>Physical<br>Violence|(2)<br>Sexual<br>Violence|(3)<br>Any<br>Violence|
|---|---|---|---|
|Δln(Uf)|-0.150**|-0.020|-0.195|
||(0.069)|(0.080)|(0.132)|
|Δln(Um)|0.177**|0.024|0.197|
||(0.071)|(0.073)|(0.118)|
|Observations|348165|268173|266517|
|Mean Violence|0.181|0.067|0.198|
|X controls|Y|Y|Y|
|Year FE|Y|Y|Y|
|CountryFE|Y|Y|Y|

_Source:_ Authors’ analysis based on data from the Demographic and Health Surveys (DHS).

# _Notes:_

* p<0.10, ** p<0.05, *** p<0.01. Standard errors are robust to arbitrary forms of heteroscedasticity and are clustered at the country level. All estimates are of equation (2). The dependent variable in each regression is a binary dummy variable taking the value one if the individual female respondent was a victim of violence, defined as physical (1), sexual (2) or either (3) in the last twelve months. X is a vector of controls for age and education of respondent, education of her spouse, and urban location. Relative to Table 1, the HP-filter detrended unemployment rates are replaced with the first difference in the logarithm of the unemployment rates.

31
a whole and each fiscal policy separately are analyzed in terms of its contribution to poverty and inequality using the Commitment to Equity (CEQ) methodology (Lustig, 2018). The study focuses on a pre-pandemic year (2019) to circumvent potential data issues and represent a relatively stable fiscal situation. 0F<sup>1</sup>

> 1 The years 2020 or 2021 witnessed substantial changes in the social safety system in Brazil. The changes were, however, temporary and the emergency programs have been lifted as of 2022. The year 2019 is also preferred because there were significant changes in the data collection approach of the national household survey that was used for this analysis. For a short presentation of those changes, see Lara Ibarra and Vale (2022).

2