rafmacalaba/datause-encoder-data huggingface dataset:
# **1 Introduction**

The rise in disability rolls in developed countries during the 1990s (OECD, 2010) combined with low levels of employment among beneficiaries prompted policy makers to examine how the design of disability insurance (DI) can facilitate the labor market reintegration of beneficiaries. Among other tools, proposals typically include improving financial incentives for work and the better identification of remaining working capacity (Autor and Duggan, 2010; Burkhauser and Daly, 2011; Maestas, 2019).

Whether low levels of reintegration result from limited working capacity, other barriers to employment or poorly designed financial incentives is an important question for policy design. To the extent that limited working capacity is the reason behind low levels of reintegration, financial incentives or periodic reassessments are unlikely to have much success in reintegrating beneficiaries into the labor market. Moreover, if they include the removal of benefits, they can harm beneficiary welfare. If, on the other hand, low levels of reintegration are caused by poorly designed incentives, such as earnings limits set too low (Krekó, Prinz and Weber, 2023), governments can improve the efficiency and fiscal sustainability of DI programs by setting incentives appropriately. But even then, supply-side financial incentives might not be effective without rehabilitation and personalized support services to mitigate other potential barriers to work, such as human capital depreciation (Edin and Gustavsson, 2008), stigma (Eriksson and Rooth, 2014; Fernández-Blanco and Preugschat, 2018) or psychological distress (Diette, Goldsmith, Hamilton and Darity Jr., 2012) caused by long-term unemployment.

In this paper, we study a unique large-scale reassessment reform to investigate the extent to which beneficiaries can be reintegrated when their benefits are removed or reduced. Starting in 2012, Hungarian DI beneficiaries under 57 years of age with health damage below 80% had to undergo a reassessment in order to remain eligible for benefits. As a result, about 18,000 beneficiaries (9% of the reassessed beneficiaries and 5% of all beneficiaries) lost their benefits while about 12,000 beneficiaries (6% of the reassessed beneficiaries and 4% of all beneficiaries) had their benefits reduced. We study the labor market consequences of benefit loss or reduction by leveraging age and health cutoffs in reassessments and focusing on a narrow age cohort around the cut-off age.

Comparing beneficiaries just below and just above the age cut-off, we find that among affected beneficiaries the probability of disability insurance receipt decreased by 1.5 percentage points due to the reform. About two-thirds of those who left DI were employed in the primary labor market or participated in public works in the post-reform period: without the concurrent receipt of DI benefits, employment increased by 0.9 percentage points, and 2
cocaine users in the US (the biggest market for cocaine) favor this explanation. For instance, hospital and coroner data show the aging of cocaine users. Also, trends in the Arrestee Drug Abuse Monitoring (ADAM) data show that the average cocaine-using offender is not only getting older, but also sicker. This evidence, together with increasing incarceration rates, has led to a slowly declining number of cocaine (and heroin) addicts.<sup>32</sup> Additional evidence also suggests that “a greater — proportion of cocaine-using population is dependent a finding that is consistent with the observation that cocaine users developed their habits over time and are now experiencing the problems that stem from longterm use” (see Reuter, 1999). What this evidence—the composition of cocaine demand by age groups and by occasional vs. dependent users—suggests is that the problem of cocaine use, at least in the US, is “increasingly a problem of long term users who developed their habits in the early stages of the epidemic” (ADAM report, 1997, cited in Reuter, 1999). However, it should be noted that the low prices of cocaine currently being observed, when compared to historical prices, might be inducing new users to try cocaine and may spur its consumption once again in the near future. The latest available indicators of cocaine consumption among 8th to 12<sup>th</sup> graders in the US show a worrisome picture: trends in 30-day and annual prevalence of cocaine and crack use increased for 10<sup>th</sup> and 12<sup>th</sup> graders in 2004, and the disapproval among 12<sup>th</sup> graders of people using cocaine occasionally or regularly, as well as their perception of risks in using cocaine, have decreased (University of Michigan, 2004).

The long-term trends in the composition of cocaine demand by age group and by occasional vs. dependent consumers illustrates an important issue, namely, that the consumption of cocaine, as observed in

> 32 See the analysis in Reuter (2001).

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- 22 -

TIableM1I Coa'd: Fel Shame InIbumu Powr OsaKa In.- O.3C.D. Ccuswul Ia 198

||CoaleNd Othe<br>Sold Fuel|Oil|Ga|Other|_Shar_of thrmal<br>in tot publi<br>power|
|---|---|---|---|---|---|
|Nige4w|0.1|19.6|803|0.0|77.6|
|Paklusa|0.6|30.5|68.9|0.0|30.4|
|PapuN.O.<br>|0.0|100.0<br>|0.0|0.0|_273_|
|Pau<br>|0.0|83.9|9.2|6.8|103|
|Phitppins|21.6|78.4<br>|0.0|0.0|45.1|
|Pueto Rico|0.0|100.0|0.0|0.0|98.2|
|Qaar<br>|0.0|6.0|94.0|0.0|100.0|
|Rwands<br>|0.0|100.0|0.0|0.0|3.4|
|S. PIee|0.0|100.0|0.0|0.0|100.0|
|So-diAmbie|0.0|92.8|7.2|0.0|100.0|
|Soopl|0.0|100.0|0.0|0.0|100.0|
|Seychelhe<br>|0.0|100.0|0.0|0.0|100.0|
|S9apor|0.0|100.0|0.0|0.0|100.0|
|SohAfrica|100.0|0.0|0.0|0.0|96.0|
|SkiLanka|0.0|100.0|0.0|0.0|03|
|Sudan|0.0|100.0|0.0|0.0|44.5|
|Thailand|27.6|19.1|_533_|0.0|77.5|
|TrIndad|0.0|23.0|77.0|0.0|100.0|
|TM"|0.0|513|48.7|0.0|98.6|
|Uruguy|0.0|64.7|0.0<br>.|35.3|0.7|
|<br>Ven_sala|0.0|40.9|59.1|0.0|51.6|
|_Zae_|0.0|100.0|0.0|0.0|3.0|
|_Zambia_|66.0<br>|34.0<br>|0.0|0.0|0.2|
|Zimbaw|100.0|0.0|0.0|0.0|46.1|

fgum: As for table 2.10.
in-person interviews, this survey includes information on the values that people find important and their viewpoints regarding different social issues. The data are collected in waves: this is not an issue since the Global Findex is structured in the same way. Thus, we consider the 3- item index measuring a national culture’s emphasis on universal freedoms in the domain of gender equality (support of women’s equal access to education, jobs and power) available at the country level. We introduce the inverse of this variable in order to capture the intensity of negative norms towards women in each specification.

To test for a mediating impact of negative social norms towards women, we re-estimate our model, including a triple interaction term that captures the interaction between gendered laws, negative social norms (the variable _Negative Attitudes_ ) and the female dummy. Each of the variables are also included in the model as two-way interaction terms as well as individual variables. The results provided in **Table 3** are unambiguous: once social norms are accounted for, the beneficial effect of equality in law for women’s financial inclusion is no longer significant. The only exception is the Pension indicator, where the coefficient on the interaction term between equality in Pension law and the _Female_ dummy becomes positive and significant. However, this coefficient is overpowered by the negative and significant coefficient on the Pension by social norms variable (the term _Negative Attitudes * WBL variable_ in the regression), as well as the triple interaction term ( _Female * WBL variable * Negative Attitudes_ ). Beyond directly preventing women from accessing financial services, gender norms may also discourage women from pursuing education, from obtaining jobs in the formal market, thus preventing women from having the basic tools necessary to utilize financial resources. This result confirms the claim of Acemoglu and Jackson (2017) who show that conflicting social norms should be considered in the law-making process in the sense that they have the potential to negate the effect of a women-friendly legal framework.

Continuing our testing of **H2** , we consider legal enforcement as a potential mediating factor between legal equality and women’s financial inclusion. To capture legal enforcement, we use the Rule of Law ( _ROL_ ) indicator provided by the World Bank’s World Governance Indicators data set. According to the data description, “Rule of law captures perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the 12
However, the average R&D expenditure as a percentage of GDP (RND _Y) is insignificant in explaining economic growth even for OECD countries. Breaking R&D expenditures into sub-fields does not alter the rcsult. table 4 eeports regression results when government funded and privately funded expenditures enter the regressions separately.12 They do not provide evidence for a significant return from privately funded or government funded R&D .Ilestment.

How can our mixed result be best interpreted? One might argue that the expenditure variable is a better proxy since manpower irr ices could be proxying the changes in human capital instead 3f R&ID capital. To check the validity of this argument, we include proxies for human capital accumulation used in Barro [1991], the primary and the secondary school enrollment rates, in the equation (2). The second column in Table 4 shows that both the secondary enrollnient rates and GSCP7085 are significant in explaining GDP growth.'<sup>3</sup> The magnitude and significance of the coefficient of GSCP7085 do not change after the inclusion of the enrollment rates. Our measure of the number of scientists and engineers employed on R&D activities is thus probably not simply playing the role of (less educated) human capital. Of course our proxies may represent highly educated human capital, but it would be hard to distinguish the inputs of highly educated human capital from R&D capital anyway.

Moreover, there is a positive case for choosing GSCP7085 or GSC17085 over RNDIY.

'<sup>2</sup> Because of the limited number of non-OECD country observations, we report the results for OECD countries only. Neither are applied and fundamental R&D investments significant in growth equations, which is not shown since it covers only 9 countries. '<sup>3</sup> Differently from Barro [1991], the fact that the primary school enrollment rates are insignificant in our regression is because our samnples are mostly OECD countries and the sample periods of the regressions is from 1970.

9
# **10. References**

Aten, B., A. Heston and R. Summers. 2002. Penn World Table Version 6.1, Center for International Comparisons at the University of Pennsylvania (CICUP).

Barro, Robert J. and Jong-Wha Lee. 2001. “International Data on Educational Attainment: Updates and Implications.” _Oxford Economic Papers_ 2001; 53: 541-563.

Bhagwati, J. 1968. The Theory and Practice of Commercial Policy: Departures from Unified Exchange Rates. Special Papers in International Economics. New Jersey: Princeton University Press.

Baumol, W.J., R.R. Nelson and E.N. Wolff. 1994. The Convergence of Productivity, Its <u>Significance and Its Varied Connotations. Oxford: Oxford University Press.</u> Beck, T., R. Levine and N. Loayza. 2000. “Finance and the sources of growth.” _Journal of Financial Economics_ . 58(1-2): 261-300.

Butkevicius, A., A. Kadri and J. Mayer. 2002. “Dynamic Products in World Exports.” United Nations Conference on Trade and Development Discussion Paper No. 159. Geneva: UNCTAD.

FUSADES (Fundación Salvadoreña para el Desarrollo Económico y Social). 2004. “Cuarta estrategia económica y social 2004-2009 oportunidades, seguridad y legitimidad: bases para el desarrollo.” El Salvador: FUSADES.

Ganslandt, M and J.R. Markusen. 2000. Standards and related regulations in international trade: A modeling approach. _Quantifying the impact of technical barriers to trade: Can it be done?_ 95135. Studies in International Economics, Ann Arbor: University of Michigan Press.

Grubel, Herbert G. and P.J. Lloyd. 1975. Intra-Industry Trade: The Theory and Measurement of <u>International Trade in Differentiated Products. New York: John Wiley & Sons.</u> Gwartney, James and Robert Lawson (2004). “Economic freedom of the world: 2004 annual report.” Vancouver: The Fraser Institute. Data retrieved from www.freetheworld.com.

Hausman, Jerry, Bronwyn H. Hall, and Zvi Griliches. 1984. “Econometric Models for Count Data with an Application to the Patents-R&D Relationship.” _Econometrica_ 52(4): 909-938.

Hausmann, R. and D. Rodrik. 2003a. “Economic development as self-discovery.” _Journal of Development Economics_ . 72: 603-633.

Hausmann, R. and D. Rodrik. 2003b. “Discovering El Salvador’s production potential.” Mimeo. Kennedy School of Government, Harvard University.

Ibeh, Kevin I.N. 2003. “Toward a contingency framework of export entrepreneurship: Conceptualizations and empirical evidence.” _Small Business Economics_ . 20: 49-68.

40
and further promote the use of public transit, the revenue raised can be used to improve access to and the quality of public transit.

Singapore adopted the first congestion pricing scheme in 1975. Some European cities have adopted area-based congestion pricing (London in 2003, Stockholm in 2006, Milan in 2008, Gothenburg in 2013). In the United States, several area-based schemes were proposed but failed to be implemented over the years. New York state’s 2019 budget proposes congestion pricing on vehicles that enter Manhattan below 60th Street. If adopted, New York City would become the first US city to use congestion pricing.<sup>15</sup> Real-time congestion pricing is now technically feasible. Singapore is slated to become the first city to use a GPS-based system in 2020 (DoT 2014). The more flexible congestion charges raise privacy concerns, however, as they rely on collecting commuters’ travel information (Parry et al. 2007).<sup>16</sup> Several studies examine the effectiveness of congestion pricing designs. They include Olszewski & Xie (2005) (Singapore), Beevers & Carslaw (2005) (London), Simeonova et al. (2018) (Stockholm), and Gibson & Carnovale (2015) (Milan). These studies find that the schemes reduce congestion by about 10–30 percent and provide significant environmental benefits for the priced area.<sup>17</sup> (For a review of studies on the impacts of existing congestion pricing schemes, see Anas & Lindsey 2011.<sup>18</sup> ) Congestion pricing has been rare in developing country. Two recent studies attempt to study the potential benefits of adopting such a policy in developing countries. Using real-time, fine-scale traffic data from Beijing, Yang et al. (forthcoming) analyze the relationship between traffic density and speed. They estimate the optimal time-varying and location-specific congestion charges to be between CNY 0.05 and CNY 0.39 per kilometer; they conclude that the 15 Several dozen high-occupancy toll (HOT) lanes with variable or dynamic tolls are operating or planned in the United States. For example, the express lanes on Interstate 66 near Washington, DC, charge singleoccupancy vehicles a fee that fluctuates according to traffic conditions.

16 Singapore’s electronic road pricing system features about 80 entry points that record passing vehicles around the city. The charges are not based on distance traveled, and they vary only infrequently. The system is being upgraded to a GPS-based system with the ability to incorporate time-varying and location-specific charges.

> 17 Drivers may respond to the charges by driving around the priced area. Such behaviors may lead to more traffic and emissions outside the area, as Gibson & Carnovale (2015) suggest.

> 18 Daniel & Bekka (2000), Bigazzi & Figliozzi (2013), and Fu & Gu (2017) study highway tolls and their environmental impacts. Using data from 98 Chinese cities, and both RD and DID methods, Fu & Gu (2017) show that eliminating highway tolls increases air pollution by 20 percent and decreases visibility by 1 kilometer.

19
in the sample. A final limitation is that while we do observe if an individual becomes infected with a curable STI, we are unable to estimate a relationship between shocks and HIV infection. This is primarily due to limitations in data - we only observe HIV status in R1 and R4 and overall prevalence in the sample is low (~3%). Despite these limitations, we believe this study does shed light on what leads women to engage in transactional sex and their reproductive health implications.

As previously noted, work by Robinson and Yeh (2011) and Dupas and Robinson (2012) shows that commercial sex workers respond to negative shocks by increasing their level of riskier and better compensated sex. They demonstrate that shocks lead to changes in the intensive margin. Of additional interest, which has implications for HIV/AIDS prevention policies, is to what extent are women entering the market for transactional sex as a response to shocks?<sup>25</sup> In other words, can we differentiate if what we are observing are changes in the extensive or intensive margin?

One way to examine whether women are entering the market for transactional sex is to restrict our analysis to women who were not engaging in transactional sex at baseline.<sup>26</sup> Specifically, we limit our analysis to women who did not exchange sex for money or gifts in the four-month period preceding the baseline survey. At the very minimum, this would eliminate any women who were active sex workers at the beginning of the study.

Table 6 presents this analysis. Overall we find results that are very similar to the ones we previously have presented. Shocks lead to higher rates of STIs (Column 1), and this effect is concentrated in unmarried women (Column 3) and those in the lowest SES groups (Column 4). Women exposed to shocks have greater levels of unprotected sex (Column 5) and unmarried women are much more likely to have been paid for sex (Column 15). These results suggest that what we are observing are changes on the extensive margin – in other words, women are entering the market for transactional sex as a response to negative shocks.

> 25 Additional work by Robinson & Yeh (2012) provides suggestive evidence that women are entering the transactional sex market in order to become better insured in the event of shocks.

> 26 At the baseline survey, data on sexual partners was collected on the 4 months leading into baseline.

17
geographical determinants. Each of the papers discussed above differs somewhat in the measures of institutions and trade used, the control variables included in the regression, and the choice of instruments. Table 1 summarizes the key differences across the main specifications of interest in each of these papers.

The top part of Tables 2 and 3 report some of the main results of these papers. To conserve on space, we report only the coefficients on the main endogenous variables of interest: institutions, trade, and their instruments in the first-stage regressions. Table 2 reports selected results from DK, while Table 3 reports selected results from RST. We do not report results from AC as we were unable to obtain their dataset at the time of writing. As a benchmark, the first two columns of Table 2 present regressions from DK in the spirit of the original AJR and FR papers, estimating the effects of institutions and trade separately, without controlling for the other variable. Specification 2.1 shows the effects of institutions only, analogous to the basic specification of AJR. The main differences with AJR is that DK use linguistic origins rather than settler mortality to instrument for institutional quality, and use a different measure of institutional quality. Nevertheless, the results are broadly similar to that of AJR. As the OLS regressions show, institutional quality is strongly positively correlated with per capita incomes. The IV regressions show a statistically and economically significant effect of institutions on per capita income, with a slope coefficient larger than the corresponding OLS estimate. Specification 2.2 shows the analog of the main FR specification. Here there are again only two differences with the original paper: the trade/GDP ratio is measured at PPP, and the only included exogenous variable is the logarithm of population. Again the results are very similar to those of the original paper, with a large and significant effect of trade on growth. In both specifications 2.1 and 2.2, the first-stage regressions of institutions and trade on their respective instruments perform quite well, with comfortably large F-statistics of 13.3 and 28.8.

Specification 2.3 reports the main DK result on the partial effects of institutions and trade. Both institutions and trade enter positively in the OLS regression, with t- statistics greater than 2. However, in the IV regression only institutional quality has a t- statistic greater than 2, while the coefficient on trade falls to near zero and the t-statistic falls to 0.3. In our other paper, we showed however that this apparent result on the importance of institutions relative to trade was quite fragile, and that both variables were 4
# **Introduction**

Poverty is the paramount indicator to gauge the socioeconomic well‐being of a population. Especially after a shock, poverty estimates can disentangle who in the population was affected how severely. As one of the main indicators for poverty, monetary poverty is measured by a welfare aggregate usually based on consumption in developing countries and a poverty line. The poverty line indicates the minimum level of welfare required for a healthy living.

Consumption aggregates are estimated traditionally by time‐consuming household consumption surveys. A household consumption questionnaire records consumption and expenditures for a comprehensive list of food and non‐food items. With around 300 to 400 items, the administering time of the questionnaire often exceeds 90 – 120 minutes. In addition to higher costs due to longer administering time, response fatigue can increase measurement error especially for items at the end of the questionnaire. In a fragile country context, a face‐to‐face time of 90 – 120 minutes can be prohibitively high. For example, security concerns restricted the duration of a visit in Mogadishu to about 60 minutes.

The extensive nature of household consumption surveys makes it difficult to obtain updated poverty estimates especially when they are needed the most: after a shock and in fragile countries. Therefore, approaches were developed to reduce administering time to allow collection of consumption data with significantly lower administering time. The most straightforward approach to minimize administering time reduces the number of items either by asking for aggregates or by skipping less frequently consumed items, called reduced consumption methodology. However, both approaches have been shown to underestimate consumption, which in turn overestimates poverty.<sup>2</sup> Splitting up the questionnaire for multiple visits is another solution but attrition issues – especially in fragile country contexts – increase required sample size and also have a high cost implication. In addition, multiple visits to the same household can increase security concerns.

A second class of approaches utilizes a full consumption baseline survey and updates poverty estimates based on a small subset of collected indicators.<sup>3</sup> These approaches estimate a welfare model on the baseline survey using a small number of easy‐to‐collect indicators. This allows updating poverty estimates by collecting only the set of indicators instead of direct consumption data. While the approach is cost‐ efficient and easy to implement in normal circumstances, the approach has two major drawbacks in the

> 2 Beegle et al, 2012.

> 3 Douidich et al, 2013; SWIFT.

2