rafmacalaba/datause-encoder-data huggingface dataset:
PRE Wor Paoer Series

|||AuIiQha||Contact<br>for_p1_e|
|---|---|---|---|---|
|WPS703|The Polit;al Economy of Fiscal<br>Policy and Inflation in Developing<br>Countries: An Empirical Analysis|Sebastian Edwards<br>Guido Tabellini|June 1991|A. Bhalla<br>37699|
|WPS704|Costs and Finance of Higher<br>Education in Pakistan|Rosemary Bellew<br>Joseph DeStefano|June 1991|C. Cristobal<br>33640|
|WPS705|What Causes Differences in<br>Achievement in Zimbabwe's<br>Secondary Schools?|Abby Rubin Riddell<br>Levi Martin Nyagura|June 1991|C. Cristobal<br>33640|
|WPS706|Successful Nutrition Programs in<br>Africa: What Makes Them Work?|Eileen Kennedy|June 1991|0. Nadora<br>31091|
|WPS707|Population, Health, and Nutrition:<br>Fiscal 1990 Sector Review|Population, Health,<br>and Nutrition Division,<br>Population and Human<br>Resources Department|June 1991|0. Na 'zra<br>31091|
|WPS708|Nongovernmental<br>Organizations and<br>Health Delivery in Sub-Saharan Africa|Jocelyn DeJong<br>|June 1991|0. Nadora<br>31091|
|WPS709|An Empirical Macroeconomic<br>Model<br>for Policy Design: The Case of Chile|Luis Serven<br>Andres Solimano|June 1991|S. Jonnakuty<br>39074|
|WPS710|Urban Property Tax Reform:<br>Guidelines and Recommendations|William Dillinger|June 1991|V. David<br>33734|
|WPS711|Financial Reform in Socialist<br>Economies in Transition|Millard Long<br>Silvia B. Sagari|June 1991|M. Raggambi<br>37657|
|WPS712|Foreign Direct Investment in<br>Developing Countries: Patterns,<br>Policies, and Prospects|Thomas L. Brewer|June 1991|S. King-Watson<br>31047|
|WPS713|The Determination<br>of Wages in<br>Socialist Economies: Some<br>Microfoundations|Simon Commander<br>Karsten Staehr|June 1991|0. Del Cid<br>39050|
|WPS714|Women in Forestry in India|Ravinder Kaur|July 1991|A. Sloan<br>35108|
|WPS715|Promoting Girl's and Women's<br>Education: Lessons from the Past<br>|Rosemary Bellew<br>Elizabeth M. King|July 1991|C. Cristobal<br>33640|
|WPS716<br>|Financing Training: Issues and<br> <br>Options<br>|Christopher Dougherty<br>Jee-Peng Tan|July 1991|C. Cristobal<br>33640|
|WPS717<br> <br>|Does Financial Liberalization Really<br>Improve Private Investment in<br>Developing Countries?|Jacques Morisset|July 1991|S. King-Watson<br>31047|
**Table 5. Tajikistan: Cargo capacity to regional markets**

||C<br>2007|argo vehi<br>|cles arrival<br>2008||Ca<br>2007|rgo vehicle<br>|s departure<br>200|8|
|---|---|---|---|---|---|---|---|---|
||With<br>goods|Empty|With<br>goods|Empty|With<br>goods|Empty|With<br>goods|Empty|
|Foreign<br>countries,o/w|7,343|310|11,110|585|2,159|4,825|2,745|8,901|
|Iran|2,786|2|2,485|2|1,027|1,762|616|1,844|
|Turkey|2,171|0|2,841|1|899|1,242|1,175|1,676|
|China|1,984|273|2,369|232|224|1,518|243|2,011|
|Afghanistan|381|34|3,392|348|9|280|711|3,351|
|CIS countries|5,340|340|4,963|255|1,961|3,448|1,806|3,164|
|Russia|172|91|272|131|41|112|14|171|
|Kazakhstan|2,137|14|1,472|16|786|1,362|802|662|
|Kyrgyzstan|1,341|221|1,662|87|713|691|742|1,030|
|Uzbekistan|1,105|10|739|5|418|702|245|495|
|Turkmenistan|527|0|762|0|2|524|0|755|
|Tajikistan|4,025|3,395|7,717|3,538|1,430|3,205|1,600|9,252|
|Total|16,708|4,045|23,790|4,378|5,550|11,478|6,151|21,317|

Source: Ministry of Transport, Tajikistan

# **Tajikistan, an economy with limited resources**

Previous works have pointed to arable land ( _T_ ), water ( _W_ ) and labor force ( _L_ ) as the main productive resources of Tajikistan (World Bank 2001, 2005). Land is used to produce cotton and other crops, water is used to irrigate agricultural parcels and generate hydroelectricity, and labor is used in production sectors (agriculture, industry and service) and temporary migration. Another important resource for the country is public finance ( _K_ ). By deciding on the allocation of public finance, the government implicitly channel the primary resources in a sector or another, hence the necessity to have a clear and sound strategy of public finance. To simplify the analysis, we will focus on the three following resources: land ( _T_ ), labor ( _L_ ) and public finance ( _K_ ).

Let consider a theoretical framework in which the major sectors of the economy (excluding public sector) are the hydropower sector, labor service abroad (temporary migration), agribusiness and industrial production. This categorization leaves out private service provision such as trade, transport and tourism but provides a minimal framework necessary to highlight the competing use of the country’s resources. Indeed, hydropower has a strong place in the government growth strategy, migration is the most profitable service activity so far, agribusiness has historical been central in the country’s production structure and industrial production is dominated by aluminum processing and light industry.

If we define by _F(.)_ the production function of a sector, we can highlight the most important production factors necessary for production ( _Y_ ). For the hydropower sector, _Y_ is assumed mainly driven by public financing to increase generation capacity and transmission lines (i.e. _Y=F(K)_ ). For labor migration, _Y_ is assumed mainly driven by private initiative through labor participation and training (general purposes and or specific skills) provided by public finance (i.e. _Y=F(L,K)_ ). For agribusiness, _Y_ is assumed mainly 18
and outflows are particularly salient to such accounting due to loss aversion and the pain of paying (Prelec and Loewenstein 1998). Through extensive field piloting of our survey tool, we identified 12 such cost categories that correspond to the way small-scale entrepreneurs typically group expenditures. The tool automatically aggregates these individual cost categories to arrive at the total cost estimate.

Finally, the “Money Left Over” section brings the previous two sections together and calculates business profits in real time. Respondents are presented a screen which shows their calculated profits and are then prompted to review and adjust previous estimates on both sales and costs. Past research has shown that such adjustment is valuable; in fact, simply relying on anchored values without dynamic adjustment often leads to final estimates that are biased toward the anchor (Tversky and Kahneman 1974; Quattrone 1982). One potential explanation for why people adjust insufficiently relates to uncertainty for the true value. For example, Quattrone et al. (1981) proposes that subjects adjust the anchor until shortly after it enters a range of plausible values for the target item. Similarly, Epley and Gilovich (2001) argue that the adjustment process comes into play when anchors are self-generated intuitive approximations. Since these values are known to be inaccurate, yet close to the correct answer, respondents adjust from the initial value until they find a plausible answer, at which point they stop (Epley and Gilovich, 2004). Another contributing factor for insufficient adjustment – e.g., in a traditional self-reported measure of business sales or profits – is a lack of cognitive resources available to the respondent for spending the required effort, which causes the adjustment to be terminated too soon and results in a final response that is too close to the anchor (Gilbert et al. 1988; Keysar, et al. 2000). For these reasons, our survey tool includes explicit prompts for respondents to go back and review previous sections with the additional reference of seeing both costs and sales together on the profit screen. Hence, automated prompts along with multiple anchors reduce the effort and cognitive costs of adjusting towards a plausible final estimate.

We test the precision of the AAA survey methodology against traditional performance measures across three independent business surveys of small firms in Ghana, Rwanda, and Uganda. By comparing answers across these sales and profits measures for the same respondent, we document substantial upward adjustment for both sales and profits and a significantly lower coefficient of 5
Results suggest that 66% of the returnees trust the Malian police and army most when it comes to providing security in the North. Almost half believe that the Malian army is brave and well trained. The vast majority of returnees believe that the government’s policies regarding reconciliation, security and social cohesion are good or very good. They also support the government’s approach towards decentralization and providing infrastructure such as access to potable water and electricity. As the next section will illustrate this differs strongly with the opinions of refugees.

# **6. Prospects for Peace**

IDPs, refugees and returnees have comparable opinions with regard to the requirements for peace: (i) addressing the ongoing crisis, (ii) improving security and (iii) reconciliation. Although there is agreement on what needs to be done, there is little consensus on what happened during the crisis, who the culprits are and who the main victims.

**Figure 15: What is the most important problem the Government needs to resolve today? (%)**

<!-- Start of picture text --> 5<br>Unemployment<br>3<br>Povery<br>6<br>1<br>Development of<br>3<br>the North 2<br>Returnees<br>26<br>Security 13<br>25 Refugees<br>17<br>Crisis in the North 56 IDPs<br>34<br>Full control over 11<br>2<br>the North 12<br>28<br>Reconciliation 24<br>15<br>0 10 20 30 40 50 60<br><!-- End of picture text --> Source: Listening to Displaced People Survey, 2014.

For instance 80% of the IDPs and returnees and 63% of the refugees in Niger report that the rebels hurt or harmed the black population in the northern Mali (Songhai, Peulh and dark skinned Kel 21
# **Tables and Figures**

Table 1: Descriptive Statistics on Countries and Data

|(1)<br>**Country**<br>**(ISO Code)**|(2)<br>**Panel**<br>**Years**|(3)<br>**GDP pc**<br>**(cons. 2010 US$)**|(4)<br>**Nbr. of**<br>**Firms**|(5)<br>**Avg. Turnover**<br>**(Thousand US$)**|(6)<br>**Net Proft**_>_**0**<br>**(%)**|(7)<br>**Max Statutory**<br>**Tax Rate(%)**|(8)<br>**Avg. ETR (%)**<br>**All frms**|(9)<br>**Avg. ETR (%)**<br>**Proftable frms**|
|---|---|---|---|---|---|---|---|---|
|Albania (ALB)|2015-2019|5_,_209_._4|19_,_237|1_,_146_._5|80_._7|15|9_._8|11_._6|
|Costa Rica (CRI)|2006-2019|10_,_047_._0|58_,_621|1_,_687_._9|79_._0|30|14_._8|18_._7|
|Dominican Rep. (DOM)|2006-2015|6_,_661_._9|38_,_028|1_,_785_._3|64_._750|27|15_._8|24_._0|
|Ecuador (ECU)|2014-2019|5_,_097_._1|48_,_477|2_,_162_._5|77_._2|28|16_._5|20_._4|
|Eswatini (SWZ)|2013-2018|4_,_773_._9|3_,_805|376_._0|66_._9|27_._5|14_._6|21_._3|
|Ethiopia (ETH)|2010-2016|514_._1|15_,_037|2_,_227_._4|70_._3|30|17_._5|24_._9|
|Guatemala (GTM)|2006-2019|3_,_413_._3|22_,_994|3_,_321_._9|67_._1|25|13_._5|18_._9|
|Honduras (HND)|2014-2019|2_,_241_._2|23_,_706|1_,_564_._5|74_._7|25<sup>_∗_</sup>|22_._2|26_._7|
|Mexico (MEX)|2010-2015|10_,_037_._2|461_,_458|3_,_077_._1|58_._5|30|12_._7|21_._1|
|Montenegro (MNE)|2011-2019|8_,_545_._5|19_,_402|607_._3|58_._9|9|2_._4|4|
|Rwanda (RWA)|2010-2017|802_._8|12_,_905|459_._080|84_._5|30|12_._1|14_._2|
|Senegal (SEN)|2010-2018|1_,_547_._1|5_,_732|3_,_641_._8|59_._2|30|27_._3|26_._8|
|Uganda(UGA)|2015-2019|956_._9|16_,_083|587_._080|62_._6|30|15_._1|22_._1|

Note: This table presents summary statistics on firms in the 13 countries in our data. All statistics are from administrative corporate tax records, except for the GDP per capita (column 4) which is from the World Development Indicators. Column (2) shows the years available in the data for each country. We use the most recent year to compute metrics shown in columns (3) to (9). The effective tax rate (ETR) can be larger than the statutory tax rate due to the reintegration of non-taxable deductions in the net profit definition (see Figure 1). This table is discussed in Section 2.1 and 2.2. Appendix B provides additional details on each country’s corporate tax system. _∗_ The maximum statutory tax rate for Honduras is 25%. However, firms paying the asset tax instead of the corporate tax face an STR that is roughly equal to 34% of that on taxable profits.
# **5. WHAT EXPLAINS DIFFERING LEVELS OF PUBLIC SUPPORT FOR REDISTRIBUTION?**

27. Data from the 2006 LiTS provide some useful insights into public attitudes towards the government’s role in tackling income inequality. Responses to the question “Do you think the state should be involved in reducing the gap between the rich and the poor?” illustrate the strong public support for redistribution: overall, only about 9 percent of respondents in EU8 countries felt the state should “not be involved” in reducing the income-gap (Chart 8), while an overwhelming majority favored either moderate or strong state involvement in reducing the income-gap between the rich and the poor.

**Chart 8: Strong public support for redistribution in EU8 countries**

<!-- Start of picture text --> EU8<br><!-- End of picture text --> <!-- Start of picture text --> Reducing income gap - share of population that would like the state to be:<br>Not involved Moderately involved Strongly involved<br>EU8<br>Slovenia<br>Lithuania<br>Latvia<br>Hungary<br>Estonia<br>Slovakia<br>Poland<br>Czech Republic<br>0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%<br><!-- End of picture text --> _Source:_ 2006 EBRD-World Bank Life in Transition Survey.

28. What are the main reasons why the extent of redistribution taking place through the tax and benefit systems is so different across countries? Clearly a multitude of factors come into play in this regard; however, an important issue is whether the general public associates poverty with factors within or outside the control of those afflicted by it. Chart 9 provides some clues why the level of public spending on benefits in Hungary and Slovenia is higher than in Slovakia and Estonia. Respondents who feel people are in need because of injustice in society are about 1.5 times as likely than others to be in favor of “strong state involvement” in reducing the income-gap between the rich and the poor (63 vs. 43 percent respectively); conversely, such respondents are only half as likely as the rest of the population to favor “no state involvement” in reducing the income-gap between the rich and poor (5 vs. 12 percent respectively).
progression) rather than educational attainment of children, and construct an index dierent from the measure of mobility used by Solon (1999) and other studies. Their index is based on the index of segregation proposed by Kremer and Maskin (1996). Their estimates are thus not comparable to the other estimates of sibling correlation in the literature, including the estimates reported in this paper. In a meta analysis of sibling correlation estimates published between 1972-2018, Prag et al. (2019) identify only two studies on developing countries including that of Dahan and Gaviria (2001), the second study is on intergenerational educational mobility in post-reform India by Emran and Shilpi (2015).

In contrast, the literature on sibling correlation in education and income in developed countries is substantial with contributions from both economists and sociologists. For surveys of this literature, please see Solon (1999), Bjorklund and Salvanes (2011), Bjorklund and Jantti (2020). Given the focus of the economic literature in developed countries on income, many of the existing studies provide estimates of sibling correlation in income. But the literature on sibling correlation in education is also large. Most of the estimates of sibling correlation in schooling in developed countries fall in the range of 0.40-0.60 (see Bjorklund and Salvanes (2011)). Among recent contributions, Grtz et al. (2021) report estimates of sibling correlation in education for 6 developed countries with an average estimate of 0.44, the lowest estimate of 0.36 (Finland) and the highest 0.51 (United States and Germany).

# (3) Conceptual Framework

# (3.1) Sibling Correlation

For the estimation and interpretation of sibling correlations, we adopt a conceptual framework that has been the workhorse in the empirical literature on sibling correlations (see, Solon et al. (1991), Solon (1999), Bjorklund et al. (2002), Bjorklund and Lindquist (2010), Mazumder (2008) and (2011)). Following Solon (1999) and Bjorklund et al. (2010), we begin with a simple model of children's educational attainment: Where _S_<sup> ̃</sup> _if_ is measure of educational attainment, usually years of schooling, of sibling _i_ in family _f_ , _μ_ is the country specic component that captures the factors common to all children 9
implicit assumption here is that Chinese producers take account of changes in the bilateral exchange rate and average domestic inflation to determine export prices. However, there could be alternative ways Chinese producers and exporters determine their destination-specific export prices. Chinese producers could be influenced just by the nominal bilateral exchange rate ( ) or by the real bilateral exchange rate ( ), with and denoting prices in importing country and China respectively. The specifications corresponding to these two ways of measuring the exchange rate are in columns [1] and [2] (for the VBI) and columns [6] and [7] (for the CBI). In both cases, the results are robust, although the magnitudes decline relative to the core specification.

Yet other models of pricing behavior could involve Chinese producers looking at changes in their multilateral competitiveness in determining destination-specific export prices. In this case, the relevant exchange rate is not destination specific but a multilateral one that is identical across all importers ( ) where stands for China’s multilateral exchange rate and hence without a subscript).<sup>13</sup> We re-estimate the core regression to cater to these possibilities by using the IMF’s effective exchange rate as the relevant measure with the nominal rate in columns [3] and [8], and the real rate in columns [4] and [9]. Again, the coefficients are correctly signed and significant at the 1 percent confidence level. Interestingly, these coefficients are substantially greater than for the core specification.

In all these specifications, exchange rates are measured as the relative price of two different currencies. An alternative way of measuring real exchange rates—sometimes called the internal real exchange rate—is as the relative price of tradables to nontradables within a country. This exchange rate is available from the Penn World Tables from the series that measures the price level of GDP.<sup>14</sup> In columns [5] and [10], we use this measure of China’s real exchange rate.

> 13 Note that in this case, the exchange rate varies across time and the index varies across importer, exporter, and product so that the interaction term exploits the variation across all four dimensions.

> 14 A higher price level is associated with a higher price of non-tradables and hence signifies an appreciation of the real exchange rate (see Rogoff, 1996). This exchange rate variable, like the IMF’s nominal and effective exchange rate series, is a multilateral variable, and hence varies only by time and not across importers.

17
a definition of participation that involves not simply<sup>reacting to policies and programs, but of shaping</sup> them: "One is not just exercising a right of assenting<sup>or dissenting from outputs or options that are</sup> already predetermined by processes over which one has no control<sup>whatsoever" (p. 16).</sup> A plurality of institutions outside of the government<sup>offers opportunities for informal</sup> representation, enabling people to "reach up" to governments.<sup>Yet although effective government</sup> provides opportunities for its citizens to make known their<sup>views, political scientists like Patrick Chabal</sup> (1986) argue that there exists "no causal link between the<sup>mechanisms of formal representation and the</sup> effectiveness of government" (p. 14). Can the development<sup>of commurity-based popular organizations</sup> reinforce accountability by constraining government agency abuses?<sup>Robin Theobald (1990) argues that</sup> basing structures of accountability in local community organizations<sup>risks their overpowerment by</sup> national needs (p. 155). However, analysis of the Asian niewly industrialized<sup>countries (NICs) suggests</sup> that their authoritarian national governments were tempered<sup>by member-controlled, local organizations</sup> that channeled rural concerns to the stace (Korten 1990). Development<sup>management analysts argue that</sup> effective interaction between local groups and government<sup>depends on formal instruments of power held</sup> by community groups: "to the extznt that they contribute<sup>to salaries, or influence promotions, or</sup> determine work priorities, local communities or groups can compel<sup>field staffs to be more responsive</sup> to their concerns" (UTphoff and Esman 1984: 148).

The development management literature documents the important<sup>role local participation plays</sup> in increasing the effectiveness of project and program<sup>decisions, not simply through accountability, but</sup> in increasing the appropriateness of project investments.<sup>A number of evaluations and studies by the</sup> World Bank and other development agencies support the<sup>view that popular participation enhances</sup> sustainability, particularly for family planning, local irrigation,<sup>agricultural extension, urban upgrading,</sup> and community water supply (see, among others, Bryant<sup>and White 1984; World Bank 1985; Midgley</sup> et al 1986). Development management researcher Louise White<sup>(1989) has outlined steps to enhance</sup> project and program accountability that substitute for hierarchical<sup>control:</sup> "mobilizing local organizations to hold managers and staff accountable;<sup>setting up procedures so that proposals by</sup> 18
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