rafmacalaba/datause-encoder-data huggingface dataset:
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Blundell, R., and Bond, S., (1998), “Initial Conditions and Moment restrictions in dynamic Panel Data Models”, Journal of Econometrics, Vol 87.

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Dreher, A., Kotsogiannis, C. and McCorriston, S., (2007), “Corruption around the World: Evidence from a Structural Model”, Economics Department Discussion Papers series, 07/02.

Heid, B., Langer, J., and Larch, M., (2011), “Income and Democracy: Evidence From System GMM Estimates’, IFO Institute Working Papers N. 118.

Huntington, S.P., (1968): “Political order in changing societies”, New haven, Yale university Pres.

Keefer, P. (2009) “Database of Political Institutions: Changes and Variable Definitions.” Development Research Group, World Bank.

Lacko, M., 2006, “Tax Rates with Corruption: Labour market Effects ; Empirical Cross-country Comparisons on OECD countries”, Institute of Economics, Hungarian Academy of Sciences, Discussion papers- 2006/4.

Leff, N., (1964), “Economic Development Through Bureaucratic Corruption”, American Behavioural Scientist , Vol (8), Number 3.

Mauro, P., (1998) “ Corruption and the composition of government expenditure”, Journal of Public Economics, 69, pp. 263-279.

Meon, P., and Weill, L.,(2008): “Is Corruption an efficient grease”, BOFIT, Intitute for Economics in Transition, Discussion Papers, 20.

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Finally, consider again figure 2b which indicates that between 1995 and 2008, these other types of import border measure were the second most frequent (after trade remedies) subject of formal WTO dispute settlement challenges by developing countries. Based on evidence from the historical pattern of WTO dispute settlement, it is likely that crisis-era border measures such as new tariffs, import quotas and bans, as well as changes to procedures for licensing or customs evaluation are likely to result in new disputes initiated by developing countries on behalf of their exporters.

# **_Crisis-induced abuses of subsidies and other behind the border measures?_**

The macroeconomic crisis and the threat of a deepening recession in 2008–2009 led many governments to adopt interventionist fiscal policies and impose other behind the border measures that may have had an impact on foreign market-access commitments in WTO-inconsistent ways. Again, the statistics compiled from the GTA (table 2) provide evidence of a number of measures that analysts could investigate systematically by sequentially addressing the technical questions (1) through (4) identified above.

Consider the broad category of subsidies. First, many national governments responded to shocks in aggregate demand by implementing sizeable stimulus packages. Some countries subsidised specific firms and industries – examples include the highly publicised US bailout of General Motors and Chrysler; the US government bailing out firms in mortgage, banking, insurance, and other areas of financial services, and the 29
approaches hold a great deal of promise; however, behavioral strategies must also be pursued. Current levels of investment in the development of new drugs, vaccines, and technologies have been at least partially fueled by the perception that behaviorallyfocused approaches cannot be made to work, or are politically and socially unviable. However, biomedical advances such as a cure for AIDS or the development of an effective AIDS vaccine are, at best, many years away or unattainable. Moreover, even once a clinic-based intervention, drug, or vaccine has been proven efficacious, changes in behavior are still needed to ensure access, uptake, and acceptability. Consequently, greater attention is now being given to a focus on behavioral change as an important component of prevention strategies and activities.

In the Tanzanian context in which the RESPECT trial was fielded, Table 1 shows that knowledge of AIDS and HIV prevention strategies is extremely high and accurate, with over 99% of respondents familiar with HIV and 85% identifying condom usage as a strategy to prevent HIV. Table 2 further shows that a large portion of young adults have been HIV tested (a national testing campaign occurred two years earlier and testing is standard during prenatal care), and people believe that HIV rates are quite high. The average respondent estimated an HIV prevalence rate of 17% among people their age in their village, indicating a high level of perceived risk. Yet table 2 also shows 20% of men admitting to multiple partners in the past month (we suspect such statistics are underreported), and close to half of participants failed to use a condom during their last sexual intercourse with a non-marital partner. These young people appear to understand their HIV risks and know how to behave to prevent transmission – yet they don‘t choose to act on that knowledge. Next we review prior experience with incentivizing individuals so as to stimulate demand for prevention.

# **Literature Review on Incentives for Health Input Behaviors and Health Outcomes**

# **_Conditional Cash Transfer Approaches_**

CCT programs which provide cash to poor households in exchange for their active participation in educational and health care services have proven remarkably popular among developing country governments, sweeping the globe from Mexico to 5
-9-

By 1981 premiums ia the Kuwaiti stock market were between 50 and 100 percent and double that in the parallel market L/ Rather than take the risk, many individual and institutional investors sold the shares forward, locking in a presumably high premium. Technically, this was a significant development for the futures market. Previously most trading was between dealers who could clear transactions with each other, but the entry of a large number of '?sellers onl)" meant that the dealers would have large open and unbalanced positions.

A significant number of the sellers were the shareholding companies. Of the 38 Gulf companies, 28 dealt in the Kuwaiti real estate and stock markets through limited liability subsidiaries 2/ . Loans were made to the subsidiary and the subsidiary invested them in the market. These companies, with a total capital of $2.5 billion, had total investments in the securities market worth $2.8 billion -- the difference funded by borrowings.

A look &t the assets of 33 nonbank KSCs demonstrates the financial involvement of Kuwaiti companies in the stock market. Between 1980 aud 1982 these firms reported a 92 percent jump in assets, from KD 1.5 billion to KD 3 billion. (Thirty-nine percent of the growth was financed from internal resources and 61 percent with short- and mediumterm loans.) Profits in 1981 and 1982 were double that of 1980, and in 1984 and 1985 losses were an equivalent amount IQ/ . The pattern parallels the rise and fall of the stock market.

Debtfo onbanks (KD million) _IV_

|SECTOR|1980|11t|192A|<br>198|1984|1985|1L98|<br>1987|
|---|---|---|---|---|---|---|---|---|
|Industrial|116|<br>129|<br>118|179|<br>164|128|113|<br>102|
|Food|78|<br>85|85|64|<br>61|57|31|<br>25|
|Service & Transport|18|<br>34|76|43|<br>44|36|53|<br>52|
|Real Estate|151|<br>217|<br>358|317|<br>297|241|186|<br>192|
|Investment|567|<br>922|<br>1084|1240|1186|1124|942|<br>1029|
|Insurance|76|<br>91|LOO|105|<br>109|92|93|<br>89|
|TOTAL|100|1478|_1iZ1_|194|181|1678|L418|1L2|

As an illustration of the diverse KSCs that were involved in the stock market, nine of fourteen industrial companies showed exceptional growth in external funding, receivables, and investments from 1979 to

- _if_ Al-Behlawi, Haze; and Riad Fahmi. The Kuwaiti Stock Market 1946-1980. The Industrial Bank of Kuwait. June 1982. P. 56.

- 2/ Securities Group SAK. Gulf Companies Direvtery. Kuwait. 1984.

- 1Q/ Based on figures from the Institute of Banking Studies. Financial Index for Kuwait Stock Exchange Listed ComDanies 80-86. Kuwait. 1987.

- / Provided by Al-Amwal.
Prevention campaigns in most countries have emphasized the message of ABC (Abstain, Be faithful, Condomize). Some assessments (for example UNDP Botswana, 2000) have concluded that the prevention campaigns have not, to date, been able to address the true underlying factors that fuel the campaign. These include intergenerational sex, poverty and the low status of women.

In recent years, most of the countries considered here have adopted a much more wide ranging multi-sectoral approach to HIV/AIDS which seeks to involve both government and civil society on a broad front. This includes an expansion of community home based care, and an expansion of life skills training, and a phased introduction of a range of treatment options. The number of Voluntary Counselling and Testing (VCT) Centers is increasing rapidly. Botswana has begun to implement a program which ultimately seeks to make AIDS treatment available to a broad sector of the population. This program is at an early stage and is not yet administering ARV treatment to very many people, but it is clear that the logistics associated with widespread ARV treatment will be formidable. The recent policy shift in South Africa is likely to lead to a rapid expansion of ARV and other forms of treatment, particularly for vulnerable groups such as pregnant or breastfeeding women.

# _1.4. HIVvaccine development_

> A number of candidate vaccines are currently in or about to begin trials. This is a result of advances in animal models and clinical research Johnston and Flores 2001). A number of vaccine candidates are ready for, or already undergoing, phase one trials in Europe, the United States and Africa. Not all HIV types are the same, and a number of different subtypes exist. These different subtypes of HIV are prevalent in different parts of the world, but candidate vaccines are often targeted at one subtype. Therefore, a vaccine may become available for some subtypes before others and thus may be used far earlier in some parts of the world. Subtype A is most prevalent in South Africa.

The current candidates are primarily aimed at subtype B, although at least one subtype A candidate has begun trials. The most advanced trials are for the phase three VaxGen candidate aimed at subtypes B and E. These are currently underway in the United States and Thailand, and interim results are expected by the end of this year Uohnston and Flores 2001). The company responsible is already planning for large scale commercial production. This, however, offers little hope to those fighting the epidemic in Africa, since the B and E subtypes are not prevalent in the African epidemic.

> In South Africa, where subtype A is dominant, phase one trials are set to begin only this year. Researchers in South Africa believe that a commercially available vaccine for use in the region is 15 to 20 years away, although there appears to be consensus that a viable vaccine can be developed (Morris, Williamson, and Vardas 2001). The South African government strongly supports the vaccine initiative and provides funds from the national budget towards its development and testing, run primarily by the South African Medical Research

6
would have been unable to make further concessions on manufactured goods’ tariff because of its customs union with the European Union. Therefore, it was assumed that other Levant countries would be reluctant to open further their markets for manufactured imports from Turkey. However, because the customs union excludes agricultural trade, Turkey would have been able to remove or significantly reduce its agricultural and food tariffs on trade within the Levant. The concessions would have been sizable as tariffs on Turkey’s imports of agricultural goods and processed foods from many of the Levant economies were much higher than tariffs on manufactured imports from these same countries (see Appendix Table A1).

This momentum for deep trade reform is reflected in the pre-simulation scenario in the following way. Tariffs on imported food and agricultural products are set to zero in the six Levant economies. Any tariff revenue loss due to this reform is assumed to be compensated by a consumption tax increase so as to keep the tax revenue constant as a share of income. Improvements in transport logistics is assumed to result in cost reductions associated with a more efficient process of shipping goods within the Levant area. The shocks are proportionate to the reductions needed to bring down the transport cost of a standard container unit to and from these countries to those of a leading country in the region, including MENA and Turkey. Information on transport costs comes from the World Bank’s Doing Business database.<sup>9</sup> In the case of exporting a container, the lowest cost country in the developing part of the Mediterranean region is Morocco. In the case of importing a container Egypt is the lowest cost country, while Jordan is the lowest cost country without access to the Mediterranean.

> 9 Unlike Balistreri, Tarr, and Yonesawa (2014) we cannot employ the database on ad valorem equivalents of the costs of time in exporting and importing as this database does not have information on four of the six Levant economies of interest to us – Lebanon, Jordan, Syria, and Iraq.

13
# **Table A5: Power Flow**

||**2020**|**2030**|**2040**|
|---|---|---|---|
|**Afghanistan to Pakistan**|8.2|11.9|10.0|
|**Bangladesh to India East**|‐1.5|‐1.4|1.1|
|**Bhutan to India East**|30.4|54.0|53.9|
|**Central Asia to Afghanistan**|17.4|3.6|4.8|
|**India East to India South**|23.5|11.7|‐15.5|
|**India North East to India East**|‐6.8|11.2|10.8|
|**India North to India East**|‐36.3|‐101.4|‐217.2|
|**India North to India West**|‐34.1|‐175.5|‐304.5|
|**India West to India East**|0.0|1.0|6.1|
|**India West to India South**|33.6|5.4|‐3.3|
|**Nepal to India East**|4.3|5.8|2.8|
|**Nepal to India North**|0.4|0.5|0.3|

## **_<u>CO2 emissions (Million tons of CO2)</u>_**

- In the baseline, the power sector is projected to emit 1.4, 2.1 and 3.4 billion tons of CO2 emissions in 2020, 2030 and 2040 respectively. India, would obviously be the largest source in the region. However, India’s share in the total regional CO2 emission from the power sector would be declining (90% in 2020 to 78% in 2040). The share would be more than doubling in Pakistan during the 2020‐2040 period (5% in 2020 to 13% in 2040). GHG emissions in Bangladesh would increase by almost five times.

## 

**TableA6: CO2 emissions from power generation (Million tons of CO2)**

||**2020**|**2030**|**2040**|
|---|---|---|---|
|**Afghanistan**|0|0|0|
|**Bangladesh**|58|161|265|
|**Bhutan**|0|0|0|
|**India**|1,263|1,856|2,667|
|**Nepal**|0|0|0|
|**Pakistan**|73|157|439|
|**Sri Lanka**|8|14|24|
|**Total**|1,401|2,188|3,395|

41
In order to ensure that the treatment and control groups are comparable in terms of observable characteristics, we implemented the following sampling procedure. First, we geographically restricted the sample to families residing in the twin cities of Gómez Palacio and Lerdo (control) and Torreón (treatment) that straddle the border of the States of Durango and Coahuila, respectively.<sup>3</sup> There are no major barriers between Gómez Palacio/Lerdo and Torreón; instead, neighborhoods spill across the two states’ border forming a single urban agglomeration. Although the two cities are split administratively between the two states, they are effectively a single urban area in socio-economic terms. In principle, households residing near the border in these cities are likely to be very similar except for the influence of state policies.

Second, we randomly drew the sample of treated households from administrative records of the universe of households that were included in _Piso Firme_ in the city of Torreon in the State of Coahuila between 2001 and 2003.<sup>4</sup> Since data collection was conducted in the spring of 2005, this time frame provides us with a sample of treated household with 2-4 years of exposure to treatment.

Third, using pre-intervention information gathered from the 2000 population census, we identified the census blocks (AGEBs) where our sample of treated households was located and calculated average pre-treatment characteristics at this census level. Similarly, we also identified a sample of census blocks in the cities of Lerdo and Gómez Palacio that were geographically close to the border with Torreón.

Fourth, using a minimum distance algorithm, we matched samples of treated and potential control census blocks using data on the following pre-treatment characteristics at the census block level: (i) proportion of blocks within each census block with dirt floors; (ii) proportion of households with dirt floors; (iii) number of children between 0 and 5 years of age; and (iv) number of households. Specifically, we calculated the distance measure as the maximum of the absolute value differences between these four variables ( _L-infinite_ distance) for each possible pair of treatment and control census blocks. We then selected as control areas those census blocks that were closest to the treated areas in terms of this distance measure. The sample of control households was

> 3 See <u>www.torreon.gob.mx/laciudad/mapas/malrededores.php.</u> 4 An important characteristic of the treatment group is its almost full level of compliance with the program.

8
the “natural resource curse” refer to Sachs and Warner, 2001) and violent conflict (Bannon and Collier, 2003), which may dampen the demand for increased female labor despite regional industrialization. A stronger argument for its inclusion comes from the work of Ross (2008) who shows that a rise in the value of oil production may reduce female labor force participation because natural resource booms result in a decline of the traded sector where, in developing economies in particular, many women tend to be employed (for example, in export‐oriented manufacturing plants) and growth in the nontraded sector (for example, sectors such as construction, from which women tend to be excluded). An important assumption of the FHS model is that the policy variable of interest should not have a direct impact on the covariate. It is for this reason that we use a measure of non‐agricultural value added at the regional level that excludes the observation of country i . For oil rents, we assume these are exogenously determined and do not anticipate that equalization of gender laws would impact them.

The application of the FHS methodology relies on a number of assumptions. According to FHS, a necessary condition for the application of their methodology is that the policy variable of interest should not have a direct impact on the covariate. We test this by regressing x�,� on the WBL index; the regression results (presented in Appendix Table A3) confirm no impact (the p‐value on the WBL index in this regression is 0.69). A second condition of the FHS approach is evidence of a pre‐trend in the covariate x�,� . We test this by regressing our covariate x�,� on the lead of the WBL index ( WBL�,���� . If there is a pre‐trend present, the coefficient on the lead of the policy variable should be statistically significant. The results from our baseline model (regression of female labor supply on the WBL index and the covariate) show that, according to the first stage of the 2SLS model, the lead of the WBL index is a significant predictor of x�,� (results presented in Table A4 in the Appendix). The results also show that the p‐value from the under‐ identification test is 0.01, suggesting that we can reject the null hypothesis of under‐identification.

In our baseline model, we do not include any other covariates; this is our preferred specification, as the only endogenous variable contained in the model is the WBL index, which we explicitly account for through the use of the FHS methodology. However, we test the robustness of our results to the inclusion of several covariates that may also be associated with women’s labor market outcomes; specifically, the fertility rate, female education, income (GDP per capita and its square term), and the male working‐age population; these are comprised in the vector Z�,� in equations (1) to (3).

18
Table 5: Fiscal (pro)cyclicality of expenditure, whole sample (2000-2016): Impacts of rigidity, fiscal space and business cycle

|Dependent variable: Cyclicalityof realgeneralgovernmentprimaryspending|(1)|(2)|(3)|
|---|---|---|---|
|Cyclicality of real GDP|0.611***|-0.407|0.402|
||(0.028)|(1.059)|(0.376)|
|**Business cycle**||||
|Crgdp*economic upturn|-0.230|2.763***|2.959*|
||(0.299)|(0.817)|(1.549)|
|Crgdp*economic upturn*rigidity||-0.047***<br>(0.017)||
|Crgdp*rigidity||0.005<br>(0.019)||
|Rigidity of public spending||-9.681<br>(6.120)||
|Crgdp*economic upturn*fiscal space|||-0.001<br>(0.002)|
|Fiscal space|||0.150<br>(0.164)|
|Crgdp*fiscal space|||0.001<br>(0.002)|
|Economic upturn|29.722|66.490*|21.955|
||(226.974)|(34.059)|(220.581)|
|Constant|-468.287|464.121|-453.536|
||(569.519)|(371.214)|(486.993)|
|Adjusted R-squared|0.071|0.013|0.078|
|Rmse|5,518|820,2|5,597|
|Joint significance (p-value)|0.00|0.002|0.000|
|CD test (p-value)|0.000|0.000|0.000|
|Order of integration|I(0)|I(0)|I(0)|
|Cluster|country|country|country|
|Covariates|Yes|Yes|Yes|
|Observations|1,954|871|1,886|
|# countries|116|54|113|

Notes. Standard errors (in parentheses) clustered at the country level. All interactive variables are also introduced in level but not reported to save space. All regressions include the volatility of the terms of trade, BD for missing data in real GDP and real expenditure series, BD for five years HP cycle correction. See Table A.1 in appendix A for further discussion on variables definition. *** p<0.01, ** p<0.05, * p<0.1.

15
|Variable|Definition|Source|
|---|---|---|
|Other|Percentage of new investment over the last year coming from other sources|Investment Climate Survey|
|Share of borrowing in foreign<br>currency|Percentage share of total borrowing (loans, accounts payable) that is denominated in foreign currency?|Investment Climate Survey|
|Necessityof collateral|Did the financingrequire collateral or a deposit? Yes(1)No(0)|Investment Climate Survey|
|**_Historical Instruments_**|||
|English Common Law|English Common Law is a dummy variable that takes the value 1 for Common Law Countries and 0 for<br>Civil Law and Socialist Law Countries|La Porta, Lopez-de-Silanes, Shleifer and<br>Vishny (1999)<br>La Porta, Lopez-de-Silanes, Shleifer and|
|Catholic|Dummy Variables that takes the value 1 if the dominant religious group in the country are Catholics|Vishny (1999)<br>La Porta, Lopez-de-Silanes, Shleifer and|
|Muslim|Dummy Variables that takes the value 1 if the dominant religious group in the country are Muslims|Vishny (1999)<br>La Porta, Lopez-de-Silanes, Shleifer and|
|Protest|Dummy Variables that takes the value 1 if the dominant religious group in the country are Protestants|Vishny (1999)|
|Ethnic Fractionalization|Ethnic Fractionalization is the probability that two randomly selected individuals in a country do not<br>belong to the same ethnic group|Alesina et al. (2003)|
|||La Porta, Lopez-de-Silanes, Shleifer and|
|Latitude|Latitude is the absolute value of the latitude of the country scaled between zero and one.|Vishny (1999)|

56