rafmacalaba/datause-encoder-data huggingface dataset:
# **Section 4: Sustainability and designs**

One very legitimate question about financial incentives to prevent undesirable behaviors is how sustainable they are in the long-term. In other words, will the beneficiaries need to be incentivized life-long or for a long period to choose the safe behavior?

Several competing hypotheses can be formulated when considering the potential longterm effects of time-limited incentives. For behaviors which individuals may not have tried until encouraged to by the incentives (e.g., use of condoms), it is possible that the incentives will induce learning and reinforcement that could result in permanent positive behavior changes even after withdrawal of the incentives. Another possibility is that positive effects would disappear after the incentives are discontinued, implying that long-term impacts can only be attained with frequent incentives.

Alternatively, psychologists have emphasized the potentially pernicious effects of extrinsic monetary incentives in destroying the intrinsic desire to engage in positive behaviors. Cameron and others (2001) review the literature on the possible destruction of intrinsic incentives that would lead to negative effects in the long term and conclude that while this might occur for some high-interest tasks, in general incentives do not have pervasive adverse effects.

Many of the evaluations reviewed in section 3 have explicitly addressed the sustainability issue by adding a post-intervention survey after the incentives were withdrawn. Among the HIV prevention incentives, the results are mixed. On the one hand, an evaluation of the medium-term impacts of the Malawi cash transfer for schooling intervention found that two years after it stopped most of the impacts reducing HIV risk were no longer present (Baird and others 2015). The increase in condom use reported among male sex workers in Mexico City was also short20
This paper aims to assess whether there is a feasible design for a two-sided market-based solution to temporary migration that would attain a basic income in the U.S. similar to current UBI proposals, such as Yang’s $1,000 a month. The paper confines attention to migration from Mexico. We envisage a market that would essentially eliminate illegal (undocumented) migration, though existing channels for permanent residence of non-citizens (”green cards”) would remain. The number of illegal migrants in the U.S. is not known with certainty, with estimates (reviewed later) in the range 11-22 million, of which around half are from Mexico. The simulations assess whether mutually beneficial trades could simultaneously provide a BIG in the U.S. and earnings gains to Mexican migrants and increased remittances to their families in Mexico. To do this, we use national surveys for 2018 to predict the expected wages of Mexican workers in the U.S., based on Mincer-type earnings regressions estimated on the U.S. survey data and the characteristics of the Mexican worker. We simulate the market when adult citizens of the U.S. can rent out their WPs,<sup>5</sup> and citizens of Mexico are allowed to purchase a yearlong WP in the U.S.

Our “benchmark” calculations restrict eligibility to those currently in the U.S. workforce. However, it can be argued that such a policy will attract citizens currently outside the workforce, to take advantage of the scope for selling their WP. We also study impacts at this extensive margin. Additionally, we consider a more restricted set of eligible Americans, namely those with dependent elderly and/or young (pre-school) children.

Armed with these data and methods, we assess whether, even when the policy is restricted to migrants from Mexico, it is possible to finance a reasonable basic income for Americans by tapping into the economic gains from migration. Costs of migrations and policy restrictions on migration create large wage gaps globally, as demonstrated by Clemens et al. <u>(2019). But are they large enough to deliver such a level of social protection in the U.S.?</u> The following section summarizes the idea in theory.<sup>6</sup> We then discuss the data and methods for the present paper (Section 3). The results are reported in Section 4, and section 5 concludes.

> 5 <u>Lokshin and Ravallion (2021) discuss this aspect of the policy design further. One can also insist that someone has</u> to have been in the workforce for some minimum period before being allowed to rent out their WP.

> 6 Section 2 draws on Lokshin and Ravallion (2021), which also provides a literature review on antecedents to the idea .

4
<!-- Start of picture text --> 40<br>Chart 6b: Science: Characteristics component of the test score<br>35 gap between students in large vs. small communities - 2003 vs.<br>2007<br>30<br>L<br>o 25<br>c<br>20<br>a<br>t 15 Science-2007<br>i Science-2003<br>10<br>o<br>n 5<br>G 0<br>a 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95<br>-5<br>p<br>Percentile<br>50<br>Chart 6c: Science: Coefficients component of the test score gap<br>between students in large vs. small communities - 2003 vs.<br>40 2007<br>L<br>o 30<br>c<br>G<br>a 20 a Science-2007<br>t<br>Science-2003<br>p<br>i<br>10<br>o<br>n<br>0<br>5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95<br>Percentile<br><!-- End of picture text -->

# _4.4. Detailed decompositions_

Tables 4a and 4b present the results of decomposing the over-time change in scores at the mean, using a standard Oaxaca decomposition methodology; the coefficients used in the decomposition were transformed using the _deviation contrast transform_ procedure (see Yun 2005)<sup>4</sup> in order to deal with the well-known “identification” problem associated with Oaxaca-type decompositions; that is, the problem arising from the dependence of the coefficients effect on the choice of reference group, when various groups of a categorical variable are involved.

Improved characteristics account for one-third of the increase in the mean mathematics score and one-quarter of the increase in the science score. Main contributors include the lower incidence of

> 4 The basic idea of Yun’s solution is to derive estimates for all possible reference groups and then derive the averaging ones; fortunately the implementation doesn’t necessarily involve tedious and repeated regressions for varying reference groups. The STATA command _Devcon_ is used for this purpose.

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to floods. This section tries to capture different aspects of this ability of poor, short to long‐term responses as a function of this ability and the feasibility of the relocation option.

The ability of the households, poor or non‐poor, would depend on factors, such as, financial resources at their disposal, early warning systems about floods, responsive administration, training given to households to enhance their coping capacity and resources to prepare for and respond to floods. Some of these aspects are shown in Table 6 below, where the sample households have been classified under three categories, Below Poverty Line (BPL) with monthly incomes below Rs. 5,000, Poor households with incomes of Rs. 5,000‐15,000 and Non‐Poor households with incomes of Rs. 15,001 and above. For the BPL and poor households, their ability to respond to floods is already limited due to lack of financial resources. Coupled with this are other factors, captured through this survey, which determine their ability to respond and cope.

Table 6: Factors determining the ability of households to respond to floods

|**Question**|**Response**|**BPL (%)**|**Poor**<br>**(%)**|**Non‐poor**<br>**(%)**|
|---|---|---|---|---|
|Aware of nearbyshelter|Yes|10.0|8.2|7.0|
|Haveyou ever shifted to shelter|yes|5.0|10.1|7.0|
|Official warningabout floods|Yes|10.0|6.6|7.0|
||Communityalarm|56.0|64.9|52.6|
|How do ou receive warnin|Cellphone|11.0|2.7|‐|
|y g|cable network|‐|5.4|10.5|
||Radio and TV|33.0|27.0|36.8|
|l d d|Less than 15 mins|50.0|66.7|44.4|
|How ong in avance o you get<br>warning|Less than 1 hour|33.3|33.3|44.4|
||12 hours before|16.7|‐|11.1|
|Wh d tt i f|Ward office|‐|3.3|2.3|
|om o you conac n case o<br>floods|Disaster control room|‐|‐|2.3|
||Local corporator|25.0|20.5|9.3|
|Trainin to coe with floods|some training|25.0|16.1|21.4|
|g p|no training|75.0|83.9|78.6|
||MCGM|25.0|81.8|83.3|
|Who has provided the training|NGO|50.0|18.2|16.7|
||Academic institute|25.0|‐|‐|
||Family and friends|36.4|56.0|37.2|
|Whom do you take loans from|Informal moneylender|9.1|5.0|7.0|
|<br>after floods|Bank|54.5|47.0|48.8|
||Microfinance or NGO|‐|1.0|2.3|
||Government|‐|2.0|2.3|

Source: Calculations based on data obtained from 200 households 20
land titling; and (3) reinforce women’s rights through a presumption that any property acquired in marriage is jointly owned by both spouses.

The LAA Act established the LAA as a one-stop shop for land registration that would provide reliable information on land ownership; expedite registration and transfer of leases; reduce registration fees; and deliver services efficiently. A fully digital register and cadaster, designed to be fully interoperable with systems held by other agencies, such as municipalities’ building registers, was established. By 2013, 18 regulations to regulate systematic land titling, planning, surveying, registry operation, and dispute resolution had been drafted and most had been adopted.

A program of systematic initial registration was designed to ensure the security of land tenure by issuing legal documents to 55,000 property owners in largely informal settlements in Maseru, a city with 300,000 inhabitants. The program was piloted in 2011 with the intent of covering all intervention areas in 2012, but contractual issues delayed the roll-out to 2013.

# **3. Data, Descriptive Evidence, and Approach**

To assess how policy reform and systematic initial registration of land rights in 2011–13 affected parcels registered, women’s co-ownership, the functioning of land and credit markets, and investment linked to land, we divided the area of interest into almost 2,000 250m x 250m blocks that serve as the basic units of analysis. Digitized administrative data for registered transactions and gridded information on built area was then aggregated to block level. Descriptive data show that 2010 policy reforms coincide with a downward shift in transaction costs; an uptick in registered sales and mortgage transactions; and a massive increase in female co-ownership. We discuss econometric strategies to examine short- and medium-term impacts and the differing contribution of 2006 and 2010 legal reforms on gender outcomes.

# **3.1 Data**

To obtain a complete set of textual and spatial data before and after the intervention, we digitized paper records from registry books for all transactions registered before LAA migrated to a functional digital platform. This provides data on the number of parcels for which rights were registered for the first time, the gender of registered rights holders, and registered sales and mortgage transactions, with attendant details for all of Maseru from 1981 through 2019.

While these data lack information on parcel attributes or the socio-economic characteristics of owners other than gender, they cover the universe of registered transactions, thus avoiding the potentially large errors, sampling and non-sampling, that would be likely in household surveys because land transfers are rare and information on land rights may not be shared with all household members. The data also include the actual 8
# **Table 6. Acceptability and Economic Burden at Prices under Consideration**

|Price|Acceptability|Strong<br>Rejection|Rejection|Barely<br>Acceptable|Acceptable|Easily<br>Acceptable|
|---|---|---|---|---|---|---|
||%|19.8|28.5|30.1|16.5|5.0|
||Income|1,087|1,301|1,490|1,548|1,434|
||avemwu|4.21|5.29|5.86|6.62|7.39|
|2.5yuan/ton|Burden|1.22|1.17|1.20|1.63|1.41|
||%|39.5|29.3|22.4|6.6|2.2|
||Income|1,225|1,372|1,575|1,431|1,372|
||avemwu|4.81|5.26|6.92|6.28|7.62|
|3yuan/ton|Burden|1.78|1.63|2.35|1.77|2.10|
||%|56.2|28.4|11.4|3.1|1.0|
||Income|1,268|1,497|1,492|1,375|1,423|
||avemwu|5.08|5.90|6.77|6.82|6.71|
|3.5yuan/ton|Burden|2.05|2.35|2.36|2.54|2.20|

# **Table 7. Burden of Poorest Households with Income Less than 400 Yuan/Month**

|Price (Yuan)|burden of<br>low-income<br>group|average<br>burden|ratio of low<br>to average|
|---|---|---|---|
|Current (2.18)|3.95|1.32|2.99|
|2.5|4.97|1.50|3.31|
|3|5.96|1.80|3.31|
|3.5|6.95|2.10|3.31|
mechanization by raising labor wages and leading firms to invest in labor-saving mechanization.<sup>2</sup> However, exogenous innovation in production techniques also leads to labor-saving mechanization that raises labor productivity, with wage increases coming as a consequence of higher productivity (Solow, 1957).<sup>3</sup> I address the problem of simultaneity by measuring how air pollution changes after an exogenous shock to wages generated by India’s Mahatma Gandhi National Rural Employment Guarantee Act (MNREGA), the world’s largest anti-poverty program. After the implementation of MNREGA, low-skill wages increased by between 4% and 8% (Imbert and Papp, 2015) in rural areas of India. I show, using a difference-in-differences framework taking advantage of the staggered roll-out of MNREGA coupled with data on nearly 1 million fires, that agricultural fires increased by between 9% and 21% after implementation of MNREGA.

To explain the mechanism, I outline a simple model showing that rising incomes could lead firms to invest in labor-saving, but polluting, mechanization. My model suggests that farmers responded to MNREGA by mechanizing harvest. This is consistent with both Hornbeck and Naidu (2014) and Clemens et al. (2018), who show that farmers mechanize after shocks to the low-skill labor market in the United States. Mechanization leads to an increase in agricultural fires in India because it leaves between 80% and 120% more biomass on a field relative to manual harvesting (Yang et al., 2008; Jitendra et al., 2017). Biomass must be removed prior to planting and fires are the least expensive way to remove biomass (Ministry of Finance, 2018). I show that fires increase by 27% in districts with the highest probability of mechanization compared to no statistically or economically significant change in districts with low probability of mechanization.

To further isolate the mechanization channel, I test for evidence of two alternative mechanisms: (1) an increase in production that may have led to more fires and (2) a shift in cropping patterns due to MNREGA’s role as implicit insurance. Increases in income driven by MNREGA may have led to changes in local demand that raised production. I show reduced form estimates of MNREGA’s impact on total hectares planted and total tonnage produced that suggest there were not large

> 2Allen (2011) argues that firms’ choice to invest in labor-saving production techniques in response to higher relative wages in England is the central reason the Industrial Revolution began there.

> 3Humphries (2013) and Kelly et al. (2014) argue that wages were not in fact higher in England at the time of the Industrial Revolution and adoption of labor-saving technology was driven by concerns other than wages. See also Voth et al. (2022). Higher subsequent wages were then a side-effect of increased labor productivity. Zheng and Kahn (2017) point out that the causality could also go in the opposite direction: firms in polluted cities in 19<sup>_th_</sup> England might have had to pay higher wages to attract workers _because_ of the pollution.

3
Figure 7: The Role of Trade for Labor Shares <!-- Start of picture text --> Routine Labor<br>Routine Labor (Adjusted for NEX)<br>Non−Routine Labor<br>Non−Routine Labor (Adjusted for NEX)<br>1990 1995 2000 2005 2010<br>Year<br>26<br>24<br>22<br>20<br>Labor Share (% of GDP)<br>18<br>16<br><!-- End of picture text --> _Notes:_ The Figure illustrates the routine and non-routine labor shares, adjusted for the role of exports. Note that the labor share is not rescaled to match the official BLS labor share and only incorporates information on earning from the CPS MORG.

industry _i_ . Thus, we can define the share of expenditure on routine and non-routine labor, _l ∈ {R, NR }_ , embodied in net exports as follows: To compute the industry specific labor income shares we use earnings data from the CPS MORG, and value added data by industry from the BEA. Trade in goods and services by industry is also obtained from the BEA.

Based on these calculations, we illustrate in Appendix C that the US is a net exporter of labor services. However, this amounts to only a small fraction of the total labor expenditure in the US. Figure 7 illustrates this finding, highlighting that trends in the net exports of goods and services only explain a very small fraction of the trends in the aggregate routine and non-routine labor shares.

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There are at least two possible explanations for the rapid escalation in the unit costs of secondary technical education in the late 1970s. One would be a decline in the number of students enrolled in such schools. UNESCO figures do, indeed, show a dramatic decline in VTE enrollments between 1977 and 1978 (UNESCO 1986), but whether this was, in fact, real or represents some sort of statistical artifact (perhaps the result of a student reclassification) is not known. In either case, a decline in the denominator (number of students) without a commensurate decline in the numerator (total expenditure) will result in an increase in expenditure per student. Unless there is reason to believe that the decline in the number of students is only a temporary phenomenon, then there can be no justification for constructing additional schools of this type. Until the costs of technical education can be brought down again (presumably by closing some of the existing VTE schools and consolidating the rest), VTE will remain a poor investment option relative to general education.

An increase in unit costs could have occurred also within the context of educational reform. As discussed in Section 2, under the reform program introduced in 1972, a number of new technical schools (ESEPs) were constructed. Given that many of these schools did not open their doors until the late 1970s, it is likely that they were not yet fully enrolled and that the high unit costs noted above do not represent the fullcapacity costs of providing this kind of education.

Moreover, to address some of the shortcomings posited above with respect to staffing, equipment, and curriculum of VTE institutions would have required (to the extent that they were, in fact, addressed) inevitably the mobilization of additional resources. The resulting increase in expenditure per student might be justified if it led to graduates of the VTE system who were truly better prepared for the world of work and who could sustain a higher level of productivity over the period of their working lives.

We do not know to what extent the higher expenditures per VTE student after 1977 represents an anomaly in the statistical series or whether more recent information will corroborate the apparent trend. If it is determined that the unit costs of secondary VTE are, indeed, on the rise in Peru, then addit'onal research will be needed that can track the occupational attainment and productivity of new output from the VTE system. All that can be said at this stage is that any significantly higher costs of producing new VTE graduates could not be justified in light of the earnings performance of existing graduates in the Peruvian work force.

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Second, we examine whether there is heterogeneity within each exporter by product types – initially high vs low quality, complex vs non-complex and new vs existing exported products. Initially low- and high-quality products are measured using their initial quality gap – the distance between their quality and the quality of the frontier (the top 10% highest quality) in the first year. The quality gaps are calculated within each HS 10-digit product and for each exporter of those products.<sup>18</sup> Product complexity is defined following Levchenko (2007) and reflects the variety of different inputs used to produce one unit of the good. Specifically, we calculate the Herfindahl index of intermediate input use using US Input-Output tables for 1997 using 496 NAICS industries. We measure complexity as the negative of the Herfindahl index, so that higher values of complexity reflect more diverse inputs (as in Levchenko, 2007).<sup>19</sup> New exported products reflect those products a country first exports after 2000, and not exported at any point during 19901999 before our sample.<sup>20</sup> We estimate product heterogeneity by interacting our robot measure with a quality gap or complex product or new product variable.

We also consider whether certain robot types matter more for quality than others. To assess this we rely on a relatively unexploited aspect of the IFR data which collects information on robot applications at the country level. Following the engineering literature, we focus on several applications which are perceived to be used mainly for improving the quality of production, notably those equipped with laser guided devices. In particular, we examine heterogeneity in quality effects of laser guided robots to non-laser guided robots within each broad application categories from the IFR data (cutting, handling and welding). Because robot applications data are at the country-level, we first construct country-level robot stocks for each application, exactly as we describe in section 3 for (overall) robot data at the country-industry level. We approximate robot applications at the country-industry-level, by multiplying the country-industry-level overall robot stock, with the (country-level) share of robots of a given application. We do so to avoid country-level regressions and enable a consistent estimation specification across regressions.

> 18 The 10% highest quality products – “the frontier” are defined as having zero quality gap.  In unreported results, our findings are robust to excluding these frontier export products.  The results are also robust to restricting to only products that at least 10 countries export in each year (see Table A7 in the Appendix).

> 19 In unreported results, we find the results are robust using the number of intermediate inputs, as an alternative measure of product complexity.

> 20 We also examine robustness to using new exports defined after 2005 or 2010 and find broadly similar results.  Most varieties are already exported before 2000.

19