rafmacalaba/datause-encoder-data huggingface dataset:
- 24 -

Table 3 Proiect sustainabiLity for social and nonsocial projects--statistical results from crosstabulations

|Pollcy<br>distortion|Like<br>sus<br>Numbe|Longer-t<br>ly to be<br>tainable<br>Row<br>r (percent)|erm<br>sustain<br>Margi<br>unce<br>sustai<br>Number|ability<br>nal<br>or<br>rtain<br>nabilitv<br>Row<br>(percent|Unlik<br>be sus<br>) Number|ely<br>to<br>tainable<br>Row<br>(percent)|C<br>X<sup>2</sup>|hi-scuare<br>ProbX<sup>2</sup>|
|---|---|---|---|---|---|---|---|---|
|Social projects<br>with data on<br>sustainabilitY<br>(N=56)|33|58.S%|16|28.6%|<br>7|12.5%|||
|Black market<br>oremiun<br>Low (Blk-50)<br>Nigh (Blk>50)<br>Chi-square|29<br>3|74.4%<br>21.4%|8<br>7|20.5%<br>50.0%|2<br>4|5.1%<br>28.6%|12.9|<br>0.00|
|Low (Blk =75)<br>High (Blk>75)<br>Chi-square|29<br>3|69.1%<br>27.3%|8<br>7|19.1%<br>63.6%|5<br>1|11.9%<br>9.09%|8.7|0.01|
|Nonsocial<br>projects<br>with data on<br>sustainabilitv<br>(N=267)|138|51.7%|81|30.3%|48|17.9%|---|---|
|Black market oremiui<br>Low (Blk-50)<br>High (Blk>50)<br>Chi-square|120<br>15|55.1%<br>37.5%|64<br>14|29.4%<br>35.0%|34<br>11|15.6%<br>27.5%|5.09|<br>0.08|
|Low (Blk-75)<br>High (8Lk>75)<br>Chi-square|121<br>14|53.8%<br>42.4%|67<br>11|29.8%<br>33.3%|37<br> <br>8|16.4%<br>24.2%|1.83|<br>0.4|
|Price distortion<br>Low (Dollar;=100)<br>High (Dollar<100)<br>Chi-square|88<br>37|57.1%<br>42.5%|45<br>28|29.2%<br>32.2%|21<br>22|13.6%<br>25.3%|6.68|<br>0.04|
|Fiscal<br>deficit<br>Low (Mbalan=-4)<br>High (Mbalan<-4)<br>Chi-square|13<br>21|65.0%<br>45.6%|4<br>14|20.0%<br>30.4%|3<br>11|15%<br>23.9%|2.09|<br>0.35|
|GDP arowth<br>High (MGDPZ'=2)<br>Low (MGDPZ<2)<br>Chi-square|51<br>6|54.8%<br>27.3%|29<br>11|31.2%<br>50.0%|13<br> <br>5|14.0%<br>22.7%|5.41|<br>0.07|

Notes: Numbers for each crosstab do not add up to the total due to missing values for policy varinoles. Chisquares and Probability>Chi-squares for each crosstab are presented. These statistics test the null hypothesis of no association between the row variable and the column variable. With degree of freedom of 1 (for dummy variable of 0 and 1); the critical value for Chi-square is 2.7 for 90 percent confidence Level.
21 reported an estimated gap of 140-150 million cubic meters in 2006 alone (Canby, et al., 2008).

China’s demand for wood has thus grown rapidly. But at the same time, its competences in wood using industries have also expanded (Table 3), so that the shortfall in supply translated into the imports of logs, as opposed to processed wood. This is evident from Figure 13 which whilst documenting a gradual increase in sawn wood imports, is most remarkable for the decline in the volume of imports of both veneer sheets and plywood, and a very rapid increase in imports of raw, unprocessed logs. China used to import plywood in the past but became a net exporter after 2001 (Adams and Ma, 2002; Changjin, et al., 2008; Kozak and Canby, 2007; White et al., 2006). However, though having developed rapidly over the past decade the Chinese wood processing industry is still not as advanced as their Northern counterparts. Consequently, whereas the North has the technology to process wood of smaller diameter and with differing wood fibre characteristics (for example, plantation wood grown in temperate climates), Chinese industries are believed to continue to demand large diameter logs from first/second growth natural forests (grown in sub-tropical and tropical climates) (Bowyer et al., 2004).

**Table 3: China’s Growing Share of Global Exports in Timber Processing Industries**

||1992|2008|
|---|---|---|
|Furniture|2.7|24.7|
|Veneer|0.7|0.1|
|Plywood|0.2|0.2|
|Fiberboard|0.5|11.4|

_Source:_ COMTRADE, accessed 17 December 2009

**Figure 13: China’s Imports of Logs and Selected Wood Products (1,000 m**<sup>**3**</sup> **)**

<!-- Start of picture text --> 18000 4500<br>16000 4000<br>14000 3500<br>12000 3000<br>10000 2500<br>8000 2000<br>6000 1500<br>4000 1000<br>2000 500<br>0 0<br>1970 1975 1980 1985 1990 1995 2000 2005<br>Logs (left) Sawnwood (right) Veneer sheets (right) Plywood (right)<br><!-- End of picture text --> _Source:_ FAO ForesSTAT data, accessed November 2009 But whilst China’s demand for timber products has grown, there has been little evidence of market access being governed by the sorts of standards affecting Gabon’s exports of timber to the EU. Instead, given the large number of companies, low barriers to entry and exit, little product differentiation, competition in the Chinese wood processing value chain is intense often leading to an erosion of profit margins.
# **Figure 14. Methodological quality of studies on people living with HIV, by country. Andean Region; 2009**

<!-- Start of picture text --> 7<br>6<br>5<br>4<br>Limited<br>Intermediate<br>3<br>High<br>2<br>1<br>0<br>Peru n= 6 Ecuador n= 5 Bolivia n= 2<br>Number of documents<br><!-- End of picture text -->

**Source:** Authors’ calculation using information from _Database and References for an Evidence-based Strategy_ in Peru, Ecuador and Bolivia.

**Findings:** Figure 14 clearly shows that no high methodologically quality studies done on people living with HIV were found in either Ecuador or Bolivia.  Hence, the evidence on people living with HIV is a major information gap in both countries.

# **General population**

In **Peru’s** database, there were 14 studies done on the general population. Thirteen of them had high methodological quality (93%); and one had intermediate quality (7%). In **Ecuador,** there were eight studies done on the general population. Five of them had high methodological quality (62.5%); one had intermediate quality (12.5%); and two had limited quality (25%). In **Bolivia** , there were seven studies done on the general population. Six of them had high methodological quality (86%); one had intermediate quality (14%) (Figure 15).

30
|Ever temporarily closed<br>during the COVID-19<br>outbreak|0.026|0.056|-0.636|0.002|0.175|-0.223|-0.824***|-0.151|
|---|---|---|---|---|---|---|---|---|
||(0.113)|(0.080)|(0.485)|(0.658)|(0.609)|(0.647)|(0.259)|(0.633)|
|Adjusting or converting their<br>production or services|0.092|-0.002|0.329|2.049***|-0.191|0.800|-0.192|0.607|
||(0.104)|(0.060)|(0.465)|(0.593)|(0.333)|(0.691)|(0.304)|(0.585)|
|Started or increased online<br>business activity|-0.093|-0.228**|0.234|-0.947*|-0.532|-1.069***|-0.600|-1.072|
||(0.141)|(0.088)|(0.452)|(0.544)|(0.347)|(0.391)|(0.396)|(0.742)|
|Started or increased delivery<br>of goods, services or carryout|-0.075|0.273***|0.083|0.515|0.209|0.506|-0.221|0.263|
||(0.079)|(0.068)|(0.391)|(0.477)|(0.267)|(0.355)|(0.514)|(0.679)|
|Started or increased remote<br>work|0.219**|-0.041|-0.789*|-1.305*|-0.074|-0.211|-0.003|0.078|
||(0.105)|(0.080)|(0.448)|(0.746)|(0.571)|(0.652)|(0.277)|(0.451)|
|Exporting directly (at least<br>10% of sales)|-0.087|-0.158***|-0.395|-0.145|-1.025*|-0.234|0.132|1.503**|
||(0.108)|(0.049)|(0.576)|(0.606)|(0.608)|(0.792)|(0.728)|(0.594)|
|Constant|-1.140**|0.224|-2.380***|-2.685|0.614|0.027|-0.954|-2.486**|
||(0.552)|(0.236)|(0.540)|(1.745)|(0.401)|(0.820)|(0.887)|(0.980)|
|Number of observations|632|262|553|223|643|264|632|261|
|r2_w|0.373|0.491|||||||
|r2_b|0.031|0.012|||||||
|r2_o|0.009|0.033|||||||
|rho|0.751|0.873|||||||

Notes: This table reports panel regressions with individual firm fixed effects for the El Salvador COV-ES data. Columns 3 through 8 report marginal effects from logistic regressions. Sampling weights from the ES are used. Standard errors are shown in parenthesis. All standard errors are clustered at survey strata, and *, **, *** denotes the significance level at 10%, 5%, and 1%, respectively. See Section 6 for more details.

49
**22 |** P a g e

excluding capital equipment. The average applied tariff rate on intermediate goods was 5 percent and that on fully processed goods was three times higher at 15 percent in 2009-10.<sup>22</sup> The level of protection afforded to raw materials is roughly similar to that of final products excluding capital goods.

**Figure 5: Salient characteristics of Sri Lanka’s MFN tariff schedule in 1998, 2001, 2003, and 2009-10**

<!-- Start of picture text --> 14.2 14.7<br>13.5<br>11.8 12.8 12.4<br>12.0 11.5<br>9.2 9.8<br>1.20 1.39 1.27 1.13 1.28<br><!-- End of picture text -->

**Right Axis** : percent of tariff lines; **Left Axis** : average applied tariff rate and coefficient of variation (ratio of standard deviation of applied tariffs to simple average applied MFN tariff rate).

Sources: Derived from the data in two successive issues of _WTO Trade Policy Review: Sri Lanka_ 2004 and 2010, Geneva Sri Lanka’s tariff structure has been driven by providing nominal protection to already existing lines of production. This does not apply only to garments but also to other sectors of the economy. In fact, sectors engaged in exports enjoy higher tariff protection than other sectors of the economy. Tariff protection implicit in Sri Lanka’s MFN tariff schedule does not extend only to import-competing industries but it also covers export sectors. Table 5 compares two average weighted applied MFN tariff rates: one weighted by imports in 2009, and another one weighted by exports both broken down to agricultural, non-agricultural products, and totals. “Exports” weighted tariff rates for both agricultural and industrial products are almost twice as high as these tariff rates weighted by their respective “imports.” This can be only explained by (a) tariffs on products exported tend to be higher than on products that are not exported (and probably not produced); (b) tariffs on exported products effectively suppress their imports; and the combination of (a) and (b).

**Table 5: MFN applied tariff rates in 2009: simple average and weighted average tariff rates (in percent) of agricultural and non-agricultural products**

||Weighted av<br>Imports|erage rates<br>exports|
|---|---|---|
|Agricultural products (HS 0 through 24)|13.4|26.1|
|Non-agriculturalproducts(HS 25 through 97)|6.0|12.4|
|Total|10.4|14.7|

Source: Own calculations based on data from the UNCTAD TRAINS database.

In other words, domestic sectors that are internationally competitive enjoy high rates of protection at home at the expense of consumers of these products. Another illustration comes from the following exercise: using the 2009 tariff schedule in six-digit HS (Harmonized System) breakdown, we have

> 22 Own estimates from data in the UNCTAD TRAINS database and WTO IDB database.
weights given **by** the structure of intra-OECD FDI flows; we set .at 4 percent. For portfolio equity liabilities **EQYL,** we set 6at **0** and measure **_Q_ by** the domestic stock market price index (in **US** dollars), when one is available; otherwise, we use the same valuation as for FDI liabilities. In turn, for portfolio assets **-** whose breakdown across debtors is unavailable **-** we take **_Q_** to equal the Morgan-Stanley world stock market index.

So far we have ignored the problem of mis-measurement of capital flows and stocks. To attempt to capture unrecorded (net) assets, we augment our measure **of** recorded non-equity assets **_LA_ by** adding to it the cumulative errors and omissions of the Balance of Payments, starting from the earliest date for which the information is available.' Finally, we complement our information on foreign asset positions with data on wealth stocks. For each country and year in our sample, we define wealth as the sum ofthe country's net foreign asset position, plus its central bank's gold holdings and the value of its physical capital stock:

**_W(j,t) = NFA(j,t)+qK(j,t)+ G(j,t)_**

(3.4) where **G** and K respectively denote gold and capital stocks, and **q** is the unit value of the latter.

To calculate these wealth stocks, we first construct estimates of each country's physical capital stock. In order to do this, we extrapolate in the time-series and cross-section dimensions the Summers-Heston PPP-based investment and **GDP** series, on the basis of available constantprice investment and per capita **GDP** data. We next construct initial capital stock estimates for those countries lacking them **by** regressing average capital-output ratios (for countries with capital stock data in Summers-Heston) on per-capita income, and using the estimated regression coefficients to project the initial (average) capital/output ratios of the remaining countries. Finally, the capital stock series is computed **by** accumulating the PPP-based real investment flows to the initial stock.

In view of the narrow scope of stock markets in developing countries, as well as in the majority of industrial countries, we value these capital stocks in the same manner as FDI stocks,

> **By** the very nature of unrecorded assets, it is impossible to know their composition **by** currency and type of financial instrument, so that in this case we do not attempt to introduce any valuation adjustment.

**15**
CLEMENS & TIONGSON

## the survey were exhausted (which occurred at 5 points from the cutoff).<sup>19</sup>

The survey was “blind” in two senses. First, no one at the survey firm knew which households were those whose member passed and which were those whose member failed. The firm was only given the name, permanent address, and phone number of the applicant. Second, the survey enumerators and respondents were told only that the study was a “follow-up survey on families of POEA job applicants”. Neither enumerators nor respondents were told that a goal of the study was to identify the effect of migration by a household member on the household.

Rough power calculations before the survey suggested a target sample size of roughly 900 households.<sup>20</sup> In the end, enumerators attempted to locate the permanent addresses of 2,053 EPS applicants, of which they successfully located and visited 1,532. Of these visits, 899 (59%) resulted in a completed survey. The rest were nonresponders— either because the residents declined to complete the survey (9%), no one was home or the residents were not the applicant’s family (15%), or neighbors indicated that the applicants’ family had once lived there but had moved away (17%) or died (0.1%). All 899 completed surveys represent the households of applicants who scored within 5 points of the cutoff.

# 5.2. Checking the discontinuity: Survey sample

Because only 59% of located addresses produced a completed survey, we must check for bias due to nonresponse. For example, if an important use of remittances were to purchase a new residence and move away, passing the test itself may affect the response rate. This could produce differences across the passing threshold not attributable to passing the test or migration.

> 19An alternative method might have led to a less representative sample. For instance, if we had provided all of the target addresses at once, the survey firm might have visited households that were easier to reach but further from the discontinuity before attempting to contact all households near the discontinuity. 20Following Duflo et al. (2007) we estimated that 900 households would give us a 92% chance of detecting a 10 percentage-point difference in household-level school enrollment fraction, a 94% chance of detecting a 10 percentage-point difference in the fraction of household engaged in entrepreneurial activity, and a 93% chance of detecting a change of 0.2 in household-level ln remittances (all at the 5% significance level).

14
<!-- Start of picture text --> — Bank of America<br>= —JPMorgan<br>s — Wells Fargo<br>Py — Wachovia i |<br>= i)) i<br>(\g , \<br>ao fat<br>PR gin ey, f<br>°<br>PPP L FHSS LZP FIL I HPSS LRGZI HGP LR FZ IES2<br><!-- End of picture text -->
ernment’s commitment to the provision of social infrastructure and services, and therefore reinforce the sense of an implicit fiscal pact between citizens and their governments. On the other hand, the lack of access to such social infrastructure may engender protest actions in the form of refusal to pay taxes to the state, as citizens judge the state as incapable of honoring the fiscal pact. Moreover, it is noteworthy to emphasize that the quality of social infrastructural services matters as well, especially in urban areas. Poor-quality service delivery, such as constant blackouts, can be viewed as evidence of government’s incompetence and may suppress citizens’ sense of national identity, or their willingness to quasi-voluntarily comply with tax policy. Evidence from the literature suggests that public goods provision is at the heart of the social contract between citizens and their respective governments (Timmons, 2005; Bratton, 2012; Timmons and Garfias, 2015). As a result, the supply of public goods can, on the one hand, induce positive attitudes among citizens toward honoring their tax obligations, while the government, on the other hand, uses the mobilized tax revenues to finance future expenditures.

In line with the above, this paper addresses two policy-relevant questions: To what extent does access to (reliable) electricity influence reported measures of tax compliance (morale) in SSA? And what are the tax-revenue implications associated with resolving the extant issues of unreliable electricity supply in the region? In other words, what are the losses in tax revenue resulting from electricity shortages and their impacts on productive sectors?

Our empirical strategy is summarized as follows: First, we explore the effects of electricity access and reliability on tax compliance attitudes of residents in SSA. With the aid of comprehensive individual-level survey data from Round 6 (2014/2015) of the Afrobarometer survey matched with secondary data on national and subnational indicators, we estimate the effect of electricity connectivity and reliability (at both the household and communal levels) on self-reported measures of tax compliance. Second, we explore the mechanisms the of access and on tax underlying effect electricity reliability compliance. Ordinary least squares (OLS) estimates of the relationship between electricity access and measures of tax compliance are plausibly biased due to the possibility of reverse causality. This limits the extent to which causal interpretations can be assigned. To overcome this challenge, we rely on the instrumental variable approach. Using geographic information system (GIS) data on the electricity transmission network in Africa, we compute the transmission network density for each second administrative boundary (i.e. district) in the region as an instrument for access and reliability of electricity. The intuition behind the instrument is that households or communities located in a district (i.e. second administrative boundaries/regions) with high transmission network density have a higher 2
Policy Research Working Paper 7131

# **Abstract**

In _Localizing Development,_ Mansuri and Rao survey theory and evidence for development strategies based on local community empowerment. This note extends their theoretical argument by focusing on local government as a vital source of new leadership. Local leaders who provide better public service can prove their qualifications for higher office, but new competition from popular local leaders may be against the interests of incumbent national leaders. Thus, decentralization reforms that could benefit economic development may face powerful resistance. International assistance should promote a balanced development of local and national governments, along with a free press to monitor government at all levels. To better inform public discussions of decentralization reforms, the World Bank should actively support research on comparative subnational politics.

This paper is a product of the Office of the Chief Economist, Development Economics Vice Presidency. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at rmyerson@uchicago.edu.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
countries.<sup>4</sup> The studies most relevant to our research are those by Ibanez et al. (2022) and Urbina Florez et al. (2023), which document PEP’s positive impacts on Venezuelan migrants’ consumption and labor income.<sup>5</sup> Secondly, we add to a vast literature examining how policy shapes fertility (e.g., Lalive and Zweim ̈uller, 2009; Milligan, 2005; Bailey, 2012). We focus on how immigration policy influences immigrant fertility. Low fertility rates and longer life spans in developed and developing countries have sparked government interest in understanding the potential role of immigration policy to bolster public pension systems. Immigration could alleviate the caused an number of retirees and could fiscal pressure by increasing support these programs through the growth of a workforce with higher fertility rates than those of natives (e.g., Storesletten, 2000). While this impact might be limited in nations with relatively low immigration and very low fertility rates (e.g., South Korea), it could be relevant for others such as Colombia.

Finally, our study contributes to a broader literature on immigrant integration(e.g.,Abramitzky et al., 2012, 2014; P ́erez, 2021). Given declining global fertility trends and increased forced it is vital to how can into host so- migration, study policy shape immigrant integration cieties. The higher fertility rates of immigrants compared to natives are controversial. This is particularly true given large migrant inflows over a short time span, as they can constrain the host country’s health care system and elicit opposition from natives.

# **II INSTITUTIONAL CONTEXT: THE PEP REGULARIZATION PROGRAM**

Colombia is the main recipient of Venezuelan migrants. According to data from the United Nations Refugee Agency, approximately 2.5 million Venezuelan migrants had arrived in Colombia by February 2022, with the vast majority arriving since 2016. This number does not include undocumented migrants who escaped detection by authorities.

> 4A related literature studies effects of migrant amnesties on crime in host communities. See Baker (2015) for the United States, Mastrobuoni and Pinotti (2015) for the European Union, and Pinotti (2017) for Italy. 5Other papers have also studied PEP’s impacts on labor outcomes (Bahar et al., 2021), political outcomes (Rozo et al., 2023), firm outcomes (Bahar et al., 2022), and inequality (Lombardo et al., 2021).

5