rafmacalaba/datause-encoder-data huggingface dataset:
|Hansen J p-value|0.163|0.173|0.376|
|---|---|---|---|
|AR1 p-value|0.00147|0.00145|0.00189|
|AR2p-value|0.203|0.193|0.170|

**Note:** This regression is performed using a system generalized method-of-moments estimators, developed by Arellano and Bovver (1995); and Blundell and Bond (1998).  The period goes from 1970 to 2020, and we constructed 13 periods, each variable for a given period representing the average on four consecutive years. **Variables -** log GDP/Capt−1   is the lag of the logarithm of GDP; **_Adj Trade_** is adjusted trade share; **_Invest (% GDP)_** is private investment measured by gross fixed capital formation in percentage of GDP; **_Human capital (%)_** represents secondary school enrollment ratio; and **_Inflation (2010 = 100)_** is Consumer Price Index. Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1. The second order lagged GDP per capita is used as an instrument for the lagged dependent variable. The lag of adjusted trade share is used as an instrument for adjusted trade share.

# **5. CONCLUSION**

This study was launched to assess the causal relationship between trade and economic growth, using IV strategies based on innovative instruments. It utilized unbalanced panel data from 197 countries for a period spanning 51 years (ending in 2020). The benefit of relying on an IV strategy is derived from its ability to address the recalcitrant problem of endogeneity in trade-growth modeling.

The findings of this study confirm the positive and significant causal impacts of trade intensity on GDP per capita. Specifically, the impact of trade intensity ranges from 0.54 and 0.76 percent for IV1 and IV2 (considering 95% confidence intervals, this ranges between 0.45 and 0.96 percent). The positive impact varies across income groups and highlights a higher positive and statistically significant impact for EMDEs. For development finance institutions, the results indicate that trade support is essential to help countries grow, especially for EMDEs. Therefore, the results also motivate the role of development finance institutions and governments in supporting trade.

There is great potential for further research in the trade-growth space. This study has assessed the causal relationship between trade and economic growth using total trade intensity (adjusted trade share) as a measure of trade. As a result, the investigation does not provide answers to other important questions regarding more specific components of trade (e.g., exports versus imports, direction of trade, composition of trade, etc.) Moreover, despite touching on country income groups, this study does not necessarily explore country or country group differences (e.g., leading sectors, products traded, etc.) that would affect individual results. In addition, research can be launched to further separate the effects of trade from other, unique, cross-border activities, such as non-trade-related capital or FDI flows. Finally, the econometric exploration of the role of the advent of internet communication, trade digitization and Artificial Intelligence appears to remain relatively untouched.

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In this paper, we have constructed and tested a methodology that computes cleanup priority indices for stockpiles of obsolete pesticides in Tunisia. Our approach integrates information on populations at risk, their proximity to stockpiles, and the relative toxic hazards of the stockpiles themselves. We have tested the robustness of our approach by varying model parameters widely and testing for stability in the rank-ordering of results. Our results indicate that the results are quite stable and robust, and we conclude that it is feasible to divide Tunisian stockpile sets into relatively unambiguous priority groups for cleanup operations. Our results also reveal a spectacular degree of clustering among the top-10 sites in Tunisia. We conclude that a sequenced strategy that follows our summary priority ordering in column 3, Table 3 can rapidly and cost-effectively decrease potential health damage from obsolete pesticide stockpiles in Tunisia.

# **References:**

- Africa Stockpiles Programme - Annual Report, July 2007 – June 2008. Available at: <u>http://www.africastockpiles.net/.</u>

- Bolt, Katharine, Piet Buys, Susmita Dasgupta, Kirk Hamilton, Craig Meisner, Kiran Pandey, Limin Wang and David Wheeler. 2003. Measuring Up: New Directions for Environmental Programs at the World Bank. World Bank Policy Research Working Paper Number 3097.

- FAO, 1995a. _Prevention of accumulation of obsolete pesticide stocks_ , Provisional Guidelines. No. 2., Food and Agriculture Organisation, Rome, Italy.  Available at:

- <u>www.fao.org/WAICENT/FAOINFO/AGRICULT/AGP/AGPP/Pesticid/Disposal/default. htm</u>

- FAO, 1995b. _Prevention and disposal of obsolete and unwanted pesticide stocks in Africa and the Near East_ , The First FAO Consultation Meeting. No. 1, Food and Agriculture Organisation, Rome, Italy. Available at:

- <u>www.fao.org/WAICENT/FAOINFO/AGRICULT/AGP/AGPP/Pesticid/Disposal/default. htm</u>

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This paper is a first step in better understanding the determinants and consequences of households’ access to mortgage markets across countries. More complete data on households’ mortgage payments and the use of other financial services will help us gain more insights. As data for 2008 and 2009 become available, the effect of the crisis on different household groups can be better assessed, especially comparing mortgage holders to others. Making the longitudinal dimension available will allow for the testing of additional hypotheses on financing constraints and tenure status. Finally, combining supply data on mortgage characteristics and interest rates with demand data as provided by SILC will be helpful to gain a more complete picture on housing finance and its economic consequences for households.

33
the 2005 PPP equivalents of the national poverty lines of the world’s 15 poorest economies in a sample of 75 national poverty lines.<sup>17</sup> The group of 15 countries was identified through a review of several alternative methods that sought to select the set of countries where there is no relationship between national poverty lines and income, thereby maintaining the principle of estimating a poverty line based the poorest countries’ evaluation of the cost of basic needs.

As our initial benchmark, we aim to keep the method and data as consistent as possible with the $1.25 line that was established by Ravallion, Chen and Sangraula (2009). To this end, we set an international poverty line based on the same 15 national poverty lines that defined the $1.25 line. Table 2 shows the national poverty lines for the 15 countries converted to USD in both 2005 and 2011 PPPs. The mean value of these lines is $1.25 in 2005 PPPs and $1.82 in 2011 PPPs.<sup>18</sup> Figure 1 plots these values and shows that $1.82 reflects a comparable average cost of basic needs for these 15 countries in 2011 PPPs as the $1.25 line did in 2005 PPPs.<sup>19</sup> For the purpose of this initial benchmark, our aim is to keep the real value of the poverty line constant for those countries that served as the basis for defining the 2005 poverty line. An important motivation for this benchmark is that global poverty goals for 2030 were announced based on the $1.25 poverty line, and the $1.82 line is our estimate of the value which keeps the goal line fixed. That is to say that, on average, among the 15 poor countries that defined the $1.25 line, $1.82 at

> 17 See Ravallion, Chen and Sangraula (2009) for details.

18 An earlier version of this paper gave estimates of $1.70 as the average of the national poverty lines in 2011 PPPs. Those estimates relied on CPIs from WDI, rather than CPIs from PovcalNet to convert the national poverty lines from their 2005 value to the 2011 value. The estimate of a 1.70 line matched the value of one of the lines prepared by Shaohua Chen for a background paper to World Bank (2014b). 19 If we re-rank the countries by mean consumption denominated in 2011 PPPs, one country in the bottom 15 changes – and the mean of the lines in 2011 PPPs becomes $1.79. In principle, one could also assert that an alternative, consistent approach to re-estimating the value of the line would be to re-estimate the relationship between national poverty lines and national income and consequently select a new sample of the poorest countries. That is to say the new line would not necessarily be based on the same 15 countries that produced the $1.25 line.

14
# **4. The Data and Estimation Strategy**

## **a. The Data**

The _baseline sample_ for the evaluation consists of the 74,000 students who were enrolled in grades 5 to 8 in any of the 328 sampled schools in January 2003. The study also involved about 3,000 upper primary teachers, of whom 445 participated in the HIV training program. In order to trace the impact of the different interventions, we collected data on several intermediate outcomes, but our main measure of whether behavior changed is the rate of childbearing among the girls enrolled in school at the baseline.

## • **Teaching about HIV/AIDS**

To determine if the teacher training intervention increased teaching about HIV/AIDS, ICS field officers conducted interviews with teachers as well as focus group discussions with students and asked whether HIV/AIDS had been mentioned in any of their classes in the past weeks. Students were also asked what they knew about HIV/AIDS, whether the teachers had mentioned condoms, and if yes, what had been said.

## • **School enrollment and attendance.**

In order to determine if reducing the cost of school reduced dropout rates, ICS field officers conducted 6 school visits, during which they conducted a roll call using the list of students enrolled at the baseline, and enquired about the whereabouts of the absent students: are they still enrolled in this school? Have they changed school? Have they dropped out?

## • **Knowledge, attitudes, and self-reported behaviors**

A Knowledge, Attitude and Practice (KAP) survey was conducted among baseline students who were still in school in 2005. The survey was a written, anonymous 13
While such differentiation is less important when it comes to tobacco products (cigarettes, cigars, chewing tobacco, etc.), differentiation in the treatment of cigarettes is found in a few countries such as Indonesia, where, presumably to encourage employment and local growers, significantly lighter taxes are imposed on cigarettes produced (especially by hand) in small local factories from locally‐grown tobacco and sold at relatively low prices. Similar features may be found in other countries: in some U.S. states, for example, where tobacco growers are important, employment and other concerns have kept taxes low, and India has long favored local and hand‐made products in its tobacco tax policy in part for employment reasons. Some countries have attempted to introduce explicit progressivity into the rate structure by imposing _ad valorem_ or price‐based specific taxes. As with many tax differentials intended to achieve non‐fiscal objectives, however, none of these features appears particularly effective in achieving the stated objectives and all tend both to complicate administration and reduce the extent to which the revenue and health objectives of tobacco taxation are achieved.

Another possible argument for multiple rates – the ‘optimal tax’ argument – is to reduce the efficiency cost of taxation by taxing products with few substitutes and lower price elasticities more heavily. As noted earlier, however, it is difficult to determine exactly what excise structure is optimal in this sense even in developed countries. Although more knowledge is better than none, and some knowledge can, as World Bank (2014) shows, be helpful in shaping some aspects of excise tax policy, when conceptual and data problems are combined with the administrative complexities to which multiple rates give rise, most developing countries seem well advised to keep their excise systems as simple and uniform as possible – for example, by taxing cigarettes on the basis of the number of units.<sup>7</sup>

# **Efficiency and Equity**

In theory, the effects of any tax on equity and efficiency – a term that encompasses both economic efficiency (the impact of taxes on the decisions of producers and consumers) and administrative and compliance efficiency (how costly it is to administer and comply with the tax system) ‐‐ depends on many other factors. Among the relevant factors are incomes, tastes and preferences (which influence the acceptability of substitute consumption goods and the distribution of the burden of taxation); the structure and technology of production (which affect the behavior of suppliers as well as production of

> 7 For a useful review of different possible bases for tobacco taxes, as well as a review of the policy and administration of such taxes in a number of Asian countries a few years ago, see Sunley (2007).

13
Table D7. Distribution of Manufacturing Establishments Motorcycles by Employment Size, Thailand <!-- Start of picture text --> NOTORCYC (VAI NOTORCYCLES FOR NESSENCER) FIENSIZE CENPLOYEES per FIN)<br>ercOlnt I<br>Cot ctt 1-19 10-49 10-W 1'°° 1W IZ00-499 100-99 1000 i Total<br>................ ........ .............. .........- ...... ------.- ........<br>YES Xlear 3 S 19 0 18 181 3 5 1 n<br>1.001 2.331 6.331 6.00 6.001 1.001 1.671 24.33<br>4 11 9.59 26.03 24.66 24.66 4.11 6.as<br>9.09 9.46 27.94 33.33 38.30 18.75 62.50<br>No | 30 g 67 1 49 1 361 29 131 3<br>10 00 22331 16.33 1 9.671 11200 3<br>1 13:22 291 2 21.59 15.86 12.78 5:73 1.32<br>1 90.91 1 90.54 1 72.06 1 66.67 1 61.70 1 81.25 1 37.50 1<br>................ ....................... ......... ..... .... ,,,,,,,,<br>Total 33 74 68 54 47 16 a 300<br>11.00 24.67 22.67 18.00 15.67 5.33 2.67 100.00<br><!-- End of picture text -->
# **1. Introduction**

Access to and use of financial services by both enterprises and households is of increasing concern to policy makers across Africa and the developing world. Recent data collection efforts on both the enterprise and household levels have enabled a more rigorous analysis (World Bank, 2007). One important dimension in the access to finance debate, which has been less analyzed, is the gender gap. Specifically, it has often been argued that lack of access to finance impedes female entrepreneurship and prevents women from participating in the modern market economy. Given the overall lack of financial service provision, with fewer than one in five households having access to formal financial services, this problem is potentially more pressing in Sub-Saharan Africa than in other developing regions of the world (Honohan and Beck, 2007).

As documented by an extensive and still growing literature, access to credit is important for firm growth, especially that of small firms (Beck, Demirguc-Kunt and Maksimovic, 2005), and for new business creation (Klapper, Laeven and Rajan, 2006). Country-specific studies and randomized field experiments confirm that access to capital can be critical for firm growth (Banerjee and Duflo, 2008; De Mel, McKenzie and Woodruff, 2008). However credit is not the only financial service that seems to matter. Recent evidence shows that access to savings services can also increase enterprise investment, especially among female entrepreneurs (Dupas and Robinson, 2009). Broad access to financial services is not only important for individuals, but also for the economy at large; credit constraints reduce the efficiency of capital allocation and intensify income inequality by impeding the flow of capital to poor individuals with investment opportunities with high expected returns (Galor and Zeira, 1993; Aghion and Bolton, 1997; Galor and Moav, 2004, Beck, Demirguc-Kunt and Levine, 2007; Lopez and Serven, 2009). Gender differences in 1
# **II. Data and Variables**

## _A. Sample_

To conduct our analyses, we build a database on bank ownership, bank valuations, and other bank-specific and country characteristics. As discussed below, information on bank ownership is particularly difficult to construct. Data permitting, we collect data on the 10 largest publicly listed banks (as defined by total assets at the end of 2001) in those countries for which LLSV (1998) assembled data on shareholder rights.<sup>6</sup> Since some countries have fewer than 10 publicly listed banks with stock market valuations, this yields 281 banks. Then, we lose 25 banks because of missing information on the book value of assets and 12 banks because of missing ownership data. The final sample consists of 244 banks across 44 countries.<sup>7</sup> Focusing on the largest banks enhances comparability across countries. Also, the largest banks tend to have the most liquid shares, reducing concerns that liquidity differences drive the results. As noted by LLSV (2002), focusing on the largest corporations should bias the results against finding a relationship between the formal legal protection of minority shareholders and valuations because larger corporations face alternative governance mechanisms, such as public scrutiny, foreign shareholders, and listings on international exchanges.<sup>8</sup>

> 6 There are five countries for which LLSV (1998) collected data on shareholder protection laws but which do not have sufficient information on bank ownership or the market valuation of banks to be included in our analyses (Belgium, Ecuador, New Zealand, Nigeria, and Uruguay). We examine the ownership of the bank holding company, not the bank itself, because bank holding company shares are publicly traded and bank holding companies control virtually all of the shares of their banks. For example, we examine Citigroup, not Citibank. If a bank is cross-listed in more than one exchange, we use market valuations from the exchange where the bank (or bank holding company) is registered. 7 The sample accounts for on average 83 percent of total banking system assets across the 44 countries.  In only five countries, does our sample cover less than 50 percent of the total banking assets of the country reported by the country’s supervisory agency (Argentina, Japan, Mexico, Pakistan, and Venezuela).  When we eliminate these countries, the results are unchanged.

> 8 Recent work on the ownership of non-financial corporations has focused on the 10 or 20 largest firms for the same reasons (LLS, 1999; LLSV, 2002). Since there are significantly fewer banks than non-financial firms, our 10-banks-per-country criterion is comparable to this research.

8
**Figure 7: Administrative Totals – Girls Enrollment Panel A**

<!-- Start of picture text --> Girls Enrollment (Grades 6-8)<br>90000<br>80000<br>70000<br>60000<br>50000<br>40000<br>30000<br>20000<br>10000<br>0<br>2003 2004 2005 2006 2007 2008<br>Rahim Yar Khan Attock Faisalabad<br><!-- End of picture text --> Source: Administrative Data. Total enrollment figures for girls in grades 6 through 8. **Panel B** <!-- Start of picture text --> Female enrollment (All grades)<br>400000<br>350000<br>300000<br>250000<br>200000<br>150000<br>100000<br>50000<br>0<br>1 2 3 4 5 6<br>ATTOCK FAISALABAD RAHIMYAR KHAN<br><!-- End of picture text --> Source: Administrative Data. Total enrollment figures for girls in all grades (kutchi to 10<sup>th</sup> grade).

39
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