rafmacalaba/datause-encoder-data huggingface dataset:
Fernandes, Ana M. (2009), “Structure and performance of the services sector in transition economies,” _Economies of Transition_ , Vol. 17(3), 467-501

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- Harris, Richard (1084), “Applied General Equilibrium Analysis of Small Open Economies with Scale Economies and Imperfect Comp,” _The American Economic Review_ , Vol. 74 (5), December, 1016-1032

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- Harrison, Glenn H., Thomas F. Rutherford and David G. Tarr. (1996), “Increased Competition and Completion of the Market in the European Community: Static and Steady-State Effects,” _Journal of Economic Integration_ , 11(3), September 1996, 332-365.

- Harrison, Glenn H., Thomas F. Rutherford and David G. Tarr (1997), “Quantifying the Uruguay Round,” _Economic Journal_ , Vol. 107 (444), September, 1405-1430.

- Harrison, Glenn H., Thomas F. Rutherford and David G. Tarr (1997a), “Economic Implications for Turkey of a Customs Union with the European Union,” _European Economic Review_ , Vol. 41(35), 861-870.

- Harrison, Glenn H., Thomas F. Rutherford and David G. Tarr (2002), “Trade Policy Options for Chile: The Importance of Market Access,” _World Bank Economic Review_ , Vol. 16, Number 1.

- Harrison, Glenn H., Thomas F. Rutherford, David G. Tarr and Angelo Gurgel (2004) “Trade Policy and Poverty Reduction in Brazil,” _The World Bank Economic Review_ , Vol. 18, 289-317, 2004.

- Hummels, David L. (2007), "Transportation Costs and International Trade in the Second Era of Globalization," _Journal of Economic Perspectives_ , Vol. 21(3), 131-154.

33
**Table 3: Average Tariffs in Sectoral Product Categories by Income Group and Region**

|||Bound Rate|||Applied Rate|||Tariff Margi|n|
|---|---|---|---|---|---|---|---|---|---|
|Country Group (No. of Countries)|All goods|Agric gds|Manuf gds|All goods|Agric gds|Manuf gds|All goods|Agric gds|Manuf gds|
|**BY INCOME LEVEL**||||||||||
|Developed economies (21)|8.5|17.3|6.6|3.4|6.2|3.2|5.1|11.1|3.4|
|Developing economies (135)|43.2|59.3|32.8|9.8|13.6|9.5|33.4|45.7|23.3|
|High income Developing (18)|26.9|37.9|25.2|7.8|9.9|7.7|19.1|28.0|17.5|
|Upper Middle income (39)|37.0|57.6|31.1|9.5|12.4|9.2|27.5|45.1|21.9|
|Lower Middle income (46)|41.6|57.1|33.0|9.8|15.5|9.3|31.8|41.7|23.7|
|Low income (32)|62.1|76.2|38.6|11.5|14.5|11.3|50.5|61.7|27.3|
|Least Developed countries (42)|61.2|76.2|41.8|12.0|15.3|11.7|49.1|60.9|30.0|
|World(156)|39.0|54.3|29.6|9.0|12.6|8.7|30.1|41.6|20.9|
|**BY REGION (Developing countries)**||||||||||
|Asia (36)|32.4|44.0|23.2|8.1|13.3|7.7|24.3|30.7|15.5|
|Latin America & Caribbean (34)|42.0|61.1|38.7|9.7|12.3|9.4|32.3|48.8|29.3|
|Europe and Middle East & N. Africa (21)|28.9|43.8|26.1|8.2|13.6|7.8|20.7|30.2|18.3|
|Sub-Saharan Africa (44)|57.4|74.5|37.0|12.2|14.9|11.9|45.2|59.6|25.0|
|**Memo:**||||||||||
|BRICS (5)|27.5|51.6|22.5|9.2|14.3|8.8|18.3|37.3|13.6|
|OPEC (12)|47.1|55.9|37.7|8.5|10.4|8.4|38.6|45.5|29.4|
|WTO (50)|46.3|61.7|30.8|9.1|14.5|8.7|37.2|47.3|22.1|

Sources: UNCTAD TRAINS (applied tariffs) and WTO IDB (bound tariffs) databases.

There are a few points to note in the regional breakdown as well. First, the few Sub-Saharan African countries that have bound tariffs have done so at levels on average higher than in the other regions. But this is due primarily because of higher bindings on agricultural products. On manufactures the highest average rates are in Latin America. Also, the simple average bound tariffs on agricultural products in Africa and Latin America tend to be much higher than in Asia.

For many developing countries tariff escalation is also an issue, as other developing countries are becoming more important as markets. Escalation is measured by calculating the average tariff rates applied to three groups of products, raw materials, intermediate products and final goods, which are defined at the BEC 2-digit level (Board Economic Categories). Table 4 summarizes the information. The table shows that by and large, and for most sectors escalation 11
% ljpos 0.257 0.405 OA52 0.649 0.567 0.545 (0387) (0389) (0372) (0.447) (0.439) (0.415) In lSenegalese Sklled 0.109 0.205 and Unffiilled) (0.143) (0.170) In (Other Afidcan -0.11B-3 -0.34E-3 Skilled and Unskilled) (0.15E-3) (0.17E-3) In (Non-African -0.01B-3 Skilied and Unskilled) (0.152-3) In (Senegalem Middle and 0882-3 Upper Management) (0.29E-3) In (Other African Middle and Upper Management) In (Non-African bMiddle and Upper Management) 0.14E-3 (0.14E3) 029E-3 (D252-3) In (Unskilled Workers) In (Sied Worers) In (Middle Management)

> (0.113) 0.029 1 0.291* (0.125) 0.17E-3 ( ).17E04 (051B-3)

**037E-3+** (0.202-3)

-033E-4 (0.19E-3)

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**(Continued)**

**I-**

**00**
Woldemichael (2024) who also use global WBES data to analyze the effect of heat on firm productivity, finding larger impacts in large firms, manufacturing, and low-income countries. In contrast to previous studies, we make four major contributions. First, we allow for nonlinear temperature response functions and model heterogeneities in country or firm typologies and temperature levels. Second, we assess the impact of yearly deviations of temperatures from locations’ long-term trends and its transmission channels such as investment, labor productivity, labor compensation, or energy costs. Third, we assess which types of firms are more exposed to climate change / less able to adapt accounting for firm characteristics, such as firms’ size, age, main sales market, resilience, and economic activity. Fourth, we assess how policy failures raise firms’ transaction costs to investment in adaptation—including access to finance, security, and business regulations—which is key to design effective policies supporting economic resilience.

# **3 Firm Choices: Location and Adaptation Investments**

The impact of local weather on a firm’s performance depends on where the firm locates and what self-protective measures it takes. Some firms may choose to gamble by investing little in self-protection while others may incur significant costs, for instance purchasing backup power generators or investing in redundant supply chains. In this section, we discuss the joint decision made by firms concerning where to locate and how much to invest in selfprotection. As we discuss below, our empirical work focuses on the set of firms who are operating in a given location at a given point in time.

Within a country, locations differ along many dimensions. Some locations may be close to final consumers while other locations may be close to export ports. Given that firms and workers compete for scarce land, the hedonic compensating differentials literature predicts that areas with productive features will have higher rents and higher wages in equilibrium, while other areas will feature lower wages and higher rents.

8
# **Entrepreneurship and Firm Formation Across Countries**

Leora Klapper, Raphael Amit, Mauro F. Guillén and Juan Manuel Quesada *

## _JEL Classification_ : G18, G38, L51, M13

_Key Words_ : Entrepreneurship, Business Statistics, Economic Development, Business Registries.

* Corresponding author:  Leora Klapper, ph: 1-202-473-8738, e-mail: lklapper@worldbank.org.  Amit and Guillén are at the Wharton School and Klapper and Quesada are at the World Bank.  We are grateful for the financial support of the SME department at the IFC, the Development Research Group at the World Bank, the Wharton Global Family Alliance, the Wharton-SMU Research Center, and the Penn Lauder CIBER Grant No P220A60017. Thanks to  Zoltan Acs, Maxwell Aitken, Laurence Carter, Tim Davis, Asli Demirguc-Kunt, Michael Ingram, Aart Kraay,  Josh Lerner,, Andrei Mikhnev, Antoinette Schoar, and participants at the NBER conference on International Differences in Entrepreneurship for valuable comments and special thanks to Sagit Stern, Sharika Jain, Dennis Bogusz and Aaron Imperiale for their outstanding research assistance.  This paper’s findings, interpretations, and conclusions are entirely those of the authors and do not necessarily represent the views of the World Bank Group or the Wharton School.
of formerly sponsored men, and they may also reflect that a husband’s income has a stronger influence on the type of dwelling in adulthood.

Impacts on consumer durables are virtually identical between formerly sponsored men and women, where estimations indicate a strong and significant impact on cell phone ownership for both genders but no effect on ownership of a bicycle, motorcycle, car, or land.

Another measure of wealth in adulthood relates to where an individual resides as an adult. Does a grown adult remain in her parents’ home, in a rented home, or in an owned home? Typically living in a home apart from parents is desirable after a certain age, especially for married couples, but this is not always economically feasible. Baseline values among the untreated show 46.8% living in the parents’ home, 23.8% living in a rented home, and 29.4 living in a home owned by the individual or jointly owned with a spouse. Table 12 shows multinomial logit estimations indicating that formerly sponsored individuals are much less likely to remain living in their parents’ home (the base category). There is some indication that women are more likely to live in an owned home, but marginal effects are insignificant. Instead of living in their parents’ home as adults at the time of the survey, sponsored individuals are 4.8 percentage points more likely to live in a home rented themselves, about two percentage point higher for men than for women.

# IV. CONCLUSION

International child sponsorship is a leading form of individual contact and financial assistance between ordinary people in developed countries and the poor in developing countries, yet little has been known about the impact of these programs on the economic outcomes in adulthood of sponsored children. Our more conservative Heckman estimates from a six-country study of 10,144 individuals show that child sponsorship is responsible for increases in monthly income of about $13–17 over an unconditional baseline of $75, or an increase of 17.3–22.9%. This effect of child sponsorship on future labor income is due principally to sponsored children entering the labor market as adults who would not have done so otherwise, particularly for women. We find that men realize an added $6.74 of monthly income from higher wages conditional upon employment but that estimations on the impact on wages of women cannot reject a null hypothesis of zero.<sup>13</sup> Given that the cost of sponsorship to sponsors was $28 per month during the time in the 1980s and 1990s when the individuals in our study were sponsored and that the average length 15
with all BE variables that are statistically significant in at least one of the two outcome regressions. We then drop those African-interaction terms, and re-run. We continue this process so that we keep only the African interaction terms that are significant in at least one of the two outcome regressions. In the end, only Capacity Agglomeration has a significant interaction term with the Africa dummy. Table 4 only presents the results of this iteration.

**Table 4. How African Countries Differ in Effects of the Business Environment**

||**L-growth**<br>||**LP-gr**<br>|**owth**|
|---|---|---|---|---|
||**coef**|**se**|**coef**|**se**|
|Security Cost|-0.076|0.049|-0.112|0.108|
|Corruption obstacle|-0.015*|0.006|0.019|0.013|
|Overdraft facility|0.014*|0.006|0.034*|0.014|
|Trade credit|-0.008|0.008|0.036*|0.016|
|Skilled labor obstacle|0.004|0.006|-0.011|0.013|
|Labor regulation obstacle|0.002|0.007|0.003|0.015|
|Tax rate obstacle|-0.007|0.007|0.008|0.015|
|Land access obstacle|-0.006|0.007|-0.002|0.014|
|Outage|-0.001|0.007|-0.003|0.013|
|Web Intensity|0.018**|0.006|0.036**|0.013|
|In Big City|0.006*|0.003|-0.001|0.005|
|Capacity agglomeration|0.042*|0.016|-0.001|0.027|
|Capacity agglomeration * Africa|0.032|0.035|0.171*|0.076|
|Inf competition|-0.012*|0.005|0.006|0.011|
|**Other controls**|**Yes**||**Ye**|**s**|
|**Industry dummies**|**Yes**||**Ye**|**s**|
|Observations|57,455||44,2|79|
|Adj. R squared|0.131||0.2|86|

*, ** represent statistical significance at the 5 and 1 percent levels. Heteroskedasticity-corrected standard errors clustered at the city level. Other controls include year dummies, missing dummy for BE variables, and base controls

Capacity agglomeration had much more positive association with labor productivity growth only in African cities. One standard deviation increase (0.12) is associated with a labor productivity growth increase of almost 2 percentage points, a considerably large effect. In other regions, the coefficient is not statistically significant, showing there is no association between capacity agglomeration and labor productivity growth. This is suggestive evidence that capacity agglomeration is a key issue for Africa. Moreover, compared to other regions, Africa shows the lowest level of capacity agglomeration (Table 5).

14
year, regulated installations must surrender allowances equivalent to their emissions. Surplus and short-falls can be matched through sales and purchases. The allowances are tracked in national registries that were linked to form a system-wide registry during the program’s second phase.

Though restrictions apply, the system is open to other tradable units established under the Kyoto Protocol, including Certified Emission Reductions (CERs) from developing countries. This is significant, since it potentially links the two types of carbon offsets into a large and liquid market, making the findings of this study relevant for developing countries. Legislation known as the “Linking Directive” lays out the relationship between EUAs and the Kyoto-system tradable units.<sup>3</sup>

# **3. The Economic Model**

The output of electricity depends upon inputs of labor and maintenance, capital service flows from generating equipment and structures, and primary fuels. In addition, under the EU ETS producers of electricity are required to obtain pollution permit allowances to offset their emissions of carbon dioxide. Hence, the disposal of the carbon dioxide by-products of electricity generation now becomes a factor of production. These observations imply the following production function for electricity: where<sup>_Yt_</sup> is output of electricity in period t,<sup>_Kt_</sup> is capital service flows,<sup>_Lt_</sup> is salaried and hourly worker services, maintenance, and non-fuel supplies,<sup>_Et_</sup> is an aggregate of energy inputs, and<sup>_Ct_</sup> is carbon emissions.

Assuming capital and labor are fixed in the short run, under duality theory the following longrun cost function exists:

> 3 For an early assessment of the ETS, see the volume edited by Ellerman, Buchner and Carraro (2007). For more on carbon markets in general, see Larson et al. (2009).

6
14

# c) _Defining the national interest and elaborating a strategic policy framework:_

National governments assume responsibility for representing the collective interests of their citizens, domestically and internationally. But understandings of what constitutes the national interest are contested and change over time.

It seems obvious that governments should approach climate change from the perspective of a rigorous assessment of their national interest – establishing their policy stance on the basis of an overall appreciation of the risks, and also the costs and benefits of potential mitigation and adaptation actions. Yet in many countries the policy stance has evolved in an ad hoc way, in response to contingent domestic political circumstances, and the need to present positions in international negotiations. In short, the vision is partial and fragmented. It has not been based on a detailed scientific, economic and political assessment. And it does not consider the ‘national interest’ in a multi‐dimensional way that includes long term considerations, and the collective good of a prosperous and peaceful international system.

Good governance on climate change requires a redefinition of national interests in light of climate change risks. This necessarily entails an effort to understand the potential implications of climate change, and the costs and benefits of possible mitigation and adaptation responses. On the basis of such effort, all governments should be able to formulate an overall perspective on the significance of human induced climate change on long term national welfare.

Some governments have concretized such a perspective by adopting an indicative temperature target – stating that their policies are intended to restrain global average temperature increases to some specified value (for example, 2 degrees centigrade for the European Union). Others have focused on specific domestic emissions reduction targets (say by 2020 and 2050). Still others have focused domestic action on adaptation. At present there is no agreed international objective in terms of a temperature target, atmospheric concentration target, or global emissions level target.

Some governments have commissioned major studies to assess climate change and evaluate appropriate responses. Prominent examples are the Stern Review (United Kingdom, 2007), the Garnaut Climate Change Review (Australia, 2008), and the earlier reports of German Parliamentary Enquete Commissions (starting in 1987).

Since climate change requires a response stretching over decades, governments need to establish a clear strategic policy framework. This can provide the stability required to encourage long term investments (in energy and infrastructure, for example) required to control emissions and to adapt to changing climates. It will also ground policy initiatives in distinctive national conditions, including important political and cultural values. Thus Australia’s strategic approach has sought to emphasize stewardship of a unique island continent; while 14
remuneration and labor conditions.

# **VI DISCUSSION**

We analyze the short-term effects of a regularization program on life outcomes of Venezuelan forced migrants in Colombia. The PEP program granted them a work permit and access to all government social programs for two years. Migrants who enrolled in the program experienced dramatic improvements in socioeconomic well-being, measured as consumption per capita and labor income, relative to other migrants. These effects seem to emerge from improved access to social public programs and financial markets as well as better employment conditions such as a higher probability of having a job and higher formalization rates. As such, migrants with a PEP visa became more self-sufficient than those without one.

PEP’s effects on the labor formalization of migrants, however, remained around 10 pp. Although this impact is not negligible, the formalization rates of regularized migrants are still one-fifth of those for the host population. This could be due to several factors. First, the pandemic and consequent economic crisis made additional job creation difficult. Second, migrants reported other hurdles that prevented them from securing formal employment, including the struggle to get a bank account. Third, some formal firms might not have recognized the validity of the PEP visa. Fourth, migrants might have been reluctant to move to formal employment as they would then have to pay taxes. Previous work by Bahar et al. (2021) suggests there is a large premium for working in Colombia’s formal sector, so the last hypothesis is an unlikely explanation. Fifth, there might not have been demand for workers in the formal sector. According to the Colombian Statistics Agency, informal employment accounted for roughly half of total employment in 2019. As such, formal jobs are probably available to individuals who have high education, are well-connected, and have been working in Colombia for many years. Forced migrants have fewer networks and—even if educated—face barriers to education certification and validation. Future research should evaluate the effectiveness of interventions that target these barriers to increase the formalization rate of forced migrants.

29
movements Mexico, Brazil and Colombia.<sup>8,9</sup> Although cointegration is sometimes given the economic interpretation of capturing “long run” relations, fundamentally it is a statistical relationship existing among non-stationary series. In our case, both relative sector sizes and the real exchange rate can plausibly be posited as I(1) and they always appear to be so in the analysis. Changing aggregate skill levels postulated in section 2 suggest no reason to assume the wages ex ante to be I(0) and even if they were, a slow adjustment process could lead to apparent non-stationary behavior within the sample analyzed.<sup>10</sup> We then use recursive cointegration estimation techniques to explore the stability of the cointegration space over time and we apply LR-test to test hypotheses on the coefficients of the cointegration vectors in order to provide empirical evidence to test the various predictions of the model and to extract some conclusions about labor market rigidities and the source of appreciations in the three countries.

# **3.1 Data**

We use quarterly data for Mexico, Brazil and Colombia on the log-transformed real exchange rate, _p_ , the wage ratio of formal over self-employed workers, _WT/WN_ , and the ratio of the absolute size of formal over the self-employed sector, _nT/nN_ . Real exchange rates where taken from IFS, all labor market data were derived from national labor force surveys ( _Pesquisa Mensual do Empreg_ o for Brazil, _Encuesta Nacional de Empleo Urbano_ for Mexico and _Encuesta Nacional de Hogares_ , Colombia). The work force was defined as only the active male population. Because we are interested in informal workers and not educated workers opening consulting firms, all workers with more than 12 years of education were dropped from the sample.

We use as a definition of informal self-employment either that size is under 6 total workers, or that the worker is not registered with social security. We might also,

> 8 The statistical concept of a long-run equilibrium underlying cointegration analysis refers to the existence of a _stationary_ relationship among two or more _non-stationary_ time series.

> 9 Appendix B contains a brief overview of the multivariate cointegration approach of Johansen (1988). 10   Theoretically, however, it is legitimate to include an I(0) variable in the cointegrating relationship, although we would expect at least one cointegrating vector to emerge that captures simply the stationary series.  In practice, these series were never stationary across our sample and the problem was moot.

20