rafmacalaba/datause-encoder-data huggingface dataset:
**Table 3.** Structural change: The role of imported intermediates

||**O**|**LS**|**2SLS(sec**|**ond stage)**|
|---|---|---|---|---|
||(1)|(2)|(3)|(4)|
||||**Panel A**<br>||
|Total imported intermediate (log)|0.193***<br>(0.038)|0.139***<br>(0.038)|0.219***<br>(0.047)|0.221***<br>(0.046)|
|constant|-1.852***|-2.268***|-3.462***|-3.493***|
||(0.578)|(0.684)|(0.815)|(0.807)|
|Controls|NO|YES|YES|YES|
|Region FE|YES|YES|YES|YES|
|Year FE|YES|YES|YES|YES|
|# Observations|1,012|889|848|848|
|R-squared|0.32|0.69|0.69|0.69|
||||**Panel B**||
|Imported intermediate from North (log)|0.129***|0.009|0.120***|0.121***|
||(0.042)|(0.039)|(0.042)|(0.042)|
|constant|-0.860|-0.315|-1.850**|-1.865**|
||(0.619)|(0.676)|(0.728)|(0.730)|
|Controls|NO|YES|YES|YES|
|Region FE|YES|YES|YES|YES|
|Year FE|YES|YES|YES|YES|
|# Observations|1,012|889|848|848|
|R-squared|0.31|0.68|0.68|0.68|
||||**Panel C**||
|Imported intermediate from South (log)|0.159***|0.168***|0.207***|0.210***|
||(0.033)|(0.032)|(0.044)|(0.043)|
|constant|-1.196**|-2.611***|3.145***|-3.180***|
||(0.478)|(0.577)|(0.753)|(0.748)|
|Controls|NO|YES|YES|YES|
|Region FE|YES|YES|YES|YES|
|Year FE|YES|YES|YES|YES|
|# Observations|1,012|889|848|848|
|R-squared|0.31|0.70|0.70|0.70|

Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.10 **_Note_** : The controls include initial industry structure, rule of law, human capital, inflation rate, mobile broadband, transport infrastructure, total natural resource rent (% GDP), and bank credit to private sector (% GDP).

20
Policy Research Working Paper 7745

# **Abstract**

Commodity traders are often the focus of popular resentment. Food price hikes in 2007–2008 resulted in protests and food riots, and spurred governments to regulate traders. In March 2011, Government of Bangladesh banned delivery order traders in the edible oils market, citing cartelization, and replaced them with a dealer’s network appointed by upstream refiners. The reform provides a natural experiment to test alternative models of marketing intermediaries. This paper develops three models and derives testable predictions about the effects of the reform on the intercept of the margin equation and passthrough of international price. Using wheat as a comparison commodity, a difference-of-difference analysis of high frequency price data shows that the reform led to (i) an increase in domestic prices and marketing margins, and (ii) a weakening of the pass-through of imported crude prices. The evidence is inconsistent with the standard double-marginalization-of-rents model wherein intermediaries exercise market power while providing no value-added services, or with a model where delivery order traders provide credit to wholesalers at below-market interest rates. The evidence supports a model where delivery order traders relax binding credit constraints faced by the wholesale traders.

This paper is a product of the Environment and Energy Team, Development Research Group. 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 authors may be contacted at fshilpi@worldbank.org.

_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
|**Ta**|**ble 3: Numbe**|**r of days of pai**|**d maternity lea**|**ve**||
|---|---|---|---|---|---|
|Dependent variable: Female<br>workers|**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|
|Number of days of paid|**0.041*****|**0.034*****|**0.033*****|**0.033*****|**0.032*****|
|maternity leave|**(0.010)**|**(0.008)**|**(0.008)**|**(0.008)**|**(0.008)**|
|GDP per capita (logs)||4.392***|4.557***|4.353***|3.394**|
|||(0.548)|(0.546)|(0.542)|(1.352)|
|Growth rate of GDP per||0.515***|0.516***|0.518***|0.456***|
|capita (%, annual)||(0.180)|(0.174)|(0.174)|(0.166)|
|Females in adult population||1.833***|1.872***|1.867***|1.712***|
|(%)||(0.470)|(0.469)|(0.467)|(0.454)|
|Number of workers (logs)||-0.022|-0.373|-0.485*|-0.452|
|||(0.298)|(0.283)|(0.290)|(0.279)|
|Female owner present Y:1||5.051***|5.003***|4.954***|4.550***|
|N:0||(0.498)|(0.492)|(0.487)|(0.488)|
|Top manager is female Y:1||13.299***|13.186***|13.185***|13.069***|
|N:0||(0.800)|(0.793)|(0.790)|(0.774)|
|Age of firm (logs)|||-0.197|-0.255|-0.338|
||||(0.379)|(0.387)|(0.385)|
|Labor productivity (logs)|||-0.227|-0.272|-0.247|
||||(0.193)|(0.199)|(0.186)|
|Exports (% of sales)|||0.029**|0.029**|0.023*|
||||(0.014)|(0.014)|(0.013)|
|Foreign ownership (%)|||0.020**|0.019**|0.020**|
||||(0.009)|(0.009)|(0.009)|
|Firm offers formal training to|||2.205***|2.096***|1.873***|
|<br>workers Y:1 N:0|||(0.573)|(0.569)|(0.562)|
|Inadequately educated<br>|||-0.184|-0.130|-0.079|
|workers: Obstacle severity||||||
|<br>(0-4 scale)|||(0.190)|(0.205)|(0.206)|
|Firm registered when started||||-0.245|-0.380|
|operations Y:1 N:0||||(1.030)|(0.999)|
|Firm experienced losses due||||0.564|0.600|
|to crime Y:1 N:0||||(0.605)|(0.609)|
|Access to finance: Obstacle||||-0.572**|-0.498**|
|severity (0-4 scale)||||(0.223)|(0.215)|
|Tax rates: Obstacle severity||||0.287|0.298|
|<br>(0-4 scale)||||(0.229)|(0.220)|
|Firm has own website Y:1||||0.587|0.486|
|N:0||||(0.549)|(0.536)|
|Fertility rate|||||0.027|
||||||(0.972)|
|Gender parity in workplace|||||0.062***|
|<br>laws||||||

55
respondents who have the most to lose from energy subsidy reforms (e.g., those who use subsidized energy sources) are just as likely to increase their support for reforms in response to information about the negative impacts of energy subsidies as those who have little to lose from reforms. Collectively, the findings from this study provide useful guidance for policy makers to consider as they try to steer their countries away from energy subsidies. There appears to be value in broad-based “reform” campaigns that inform the general population about the negative impacts of energy subsidies and that implement credible alternative policies.

This study contributes to the existing knowledge base in at least two ways. First, this is the largest cross-country survey examining attitudes toward energy subsidy reforms, and it provides novel insights into the similarities (and differences) in levels of support for reform, as well as the characteristics and beliefs associated with support across middle-income countries. There is an absence of standardized, cross-country evidence as prior research has typically involved detailed case studies in specific countries (e.g., Inchauste and Victor 2017), and survey work examining public support for reforms has been limited; some examples of surveys include Aklin et al. (2015) for India; Pradiptyo et al. (2016) for Indonesia; and McCulloch et al. (2021) for Nigeria. Two very recent cross-country surveys have begun to fill this knowledge gap. One study across five middle-income countries involving a brief survey showed that levels of public support for energy subsidy removal were similar to levels of support for carbon taxation (Harring et al. 2023). The other study focused on Latin American countries (Vieites et al. 2023) and found a lack of knowledge about subsidies and low levels of support for reform. The current study builds on this prior work by systematically studying support for energy subsidy reform in more detail and across a much larger number and more diverse set of countries, thereby generating novel evidence that is likely to have considerable external validity in other settings and over time. For example, the survey has been designed to illustrate how people’s support for subsidy reform varies based on the main type of energy subsidized in their country, and the types of accompanying policies that people prefer (e.g., cash transfers, tax cuts, or better services). Further, the anatomy of 6
15

# _3.2 Impacts of Fuel Tax on Travel Demand, Fuel Consumption and Emissions_

Although the fuel tax is introduced mainly to generate government revenues, it could have significant impact toward the reduction of emissions and traffic congestion. A number of existing studies (e.g., Eltony, 1993; Hirota et al., 2003; Sterner, 2006) demonstrate how the fuel tax reduces travel demand, fuel consumption, and emissions. Employing an econometric model for household gasoline demand in Canadian provinces for 1969-1988, Elton (1993) finds that a 10% increase in the fuel price would cause 75% of households to reduce their vehicle travel within one year after the fuel price increase. As a result, 15% of households shifted from large to small vehicles, and 10% of households switched from less fuel-efficient to more efficient vehicles. Using the data from 68 large cities worldwide, Hirota et al. (2003) demonstrate that for every 1% increase in the fuel tax, vehicle miles traveled (VMT) could be reduced by 0.042%. Fuel taxes have played an important role in restraining growth in transport sector fuel consumption and associated carbon emissions in OECD countries. Sterner (2006) calculates that had the different OECD countries introduced a gasoline tax at the level of EU countries, such as Italy, the United Kingdom, and the Netherlands, gasoline consumption would have been reduced by 57% in the United States; 36% on average in Canada, Australia and New Zealand; 34% in Japan and 44% in the OECD as a whole. Since CO2 emissions are directly linked with fuel consumption, this would translate into a substantial reduction in CO2 emissions from the transport sector. Sterner also estimates that if all OECD countries had a low gasoline tax as does the United States, the total OECD gasoline consumption would have been 31% higher. These findings demonstrate the positive impacts of fuel taxes in fuel consumption and atmospheric emissions from the transport sector.
|**(Intercept)**|5.038***|2.456***|2.581***|
|---|---|---|---|
||(0.014)|(0.008)|(0.008)|
|**Top down/Control**|0.254***|0.124***|0.130***|
||(0.021)|(0.012)|(0.012)|
|**Bottom up/Control**|0.189***|0.108***|0.081***|
||(0.021)|(0.013)|(0.012)|
|**Female**|0.101***|0.025|0.076***|
||(0.026)|(0.015)|(0.015)|
|**Top down/Control x female**|-0.075*|-0.041|-0.034|
||(0.038)|(0.022)|(0.021)|
|**Bottom up/Control x female**|-0.106**|-0.053*|-0.054*|
||(0.039)|(0.023)|(0.022)|
|**N**|65429|65432|65430|
|**p**|0.0|0.0|0.0|
|**Log-likelihood**|-133329.6|-98882.4|-96112.6|
|**AIC**|266673.3|197778.9|192239.1|

Notes: Each column shows an OLS model predicting the three dependent variables: tax fine, tax morale and the tax index summing the other two dependent variables. The experimental treatment are interacted with gender. The results show that the treatments are generally somewhat less effective for women.

# **Conclusion**

Tax morale is an important phenomenon to understand, both for policy makers and academic researchers as well as the broader public. Here, we have documented experimental evidence from 50 countries about two interventions that, on average, generate significant increases in surveybased measure of tax morale: a participatory intervention allowing citizens to voice their expenditure preferences, and a top-down accountability intervention which increases the salience of anti-corruption efforts. We interpret our results as showing that even relatively short, shallow interventions can affect beliefs and attitudes about tax morale substantially. In our view, this suggests that similar interventions could potentially be successful at increasing tax morale in realworld environments.

Some strengths and limitations of our study are inherent in the research design and method itself. On the positive side, the online survey technology employed here is relatively cost-effective (<1 USD per complete response), allowing us to scale the research design. On the other hand, due to the survey technology, we cannot gather many covariates, control attrition effectively or tap tax morale in a more direct, behavioral fashion. However, the characteristics of our research design are also related to two key contributions of the paper.

First, in our view, one important strength of the study is the extreme diversity of respondents in our sample: while previous studies especially on participatory interventions had typically been confined to very specific laboratory and political settings, we are able to document that our effects are relatively comparable, though by no means equal, across a very wide range of countries and contexts. Given that it is _ex ante_ unclear how much homogeneity there is in responses to tax morale interventions, we believe that our results are a significant step forward.

18
# **Table 3. Changes in Revenue Growth Across the Business Cycle on Public Consumption: Elasticities from Fixed Effects and IV Regressions for Emerging and Advanced Economies**

|VARIABLES|(1)<br>Emerging<br>economies -<br>FE|(2)<br>Advanced<br>economies -<br>FE|(3)<br>Emerging<br>economies -<br>IV|(4)<br>Advanced<br>economies -<br>IV|
|---|---|---|---|---|
|Revenue Growth * Exp|0.31<br>[0.104]***|0.37<br>[0.081]***|0.89<br>[0.177]***|0.40<br>[0.086]***|
|Revenue Growth * Rec|-0.11<br>[0.169]|-0.01<br>[0.098]|0.09<br>[0.241]|-0.27<br>[0.153]*|
|Lagged Public Consumption Growth|-0.02|0.31|-0.07|0.31|
||[0.060]|[0.094]***|[0.062]|[0.115]***|
|Lagged General Government Expense Growth|0.05|0.02|0.06|0.01|
||[0.034]|[0.062]|[0.058]|[0.057]|
|Constant|0.04<br>[0.005]***|0.01<br>[0.002]***|||
|Observations|791|432|784|418|
|R-squared|0.050|0.190|||
|Number of countries|39|18|39|18|
|Country Fixed Effect|Yes|Yes|Yes|Yes|
|Adjusted R-squared|||-0.337|0.108|
|**First Stage IV Estimates**|||**First Stage **|**First Stage **|
|Trade Weighted Growth * Exp|||1.43<br>[.21]***|1.32<br>[.08]***|
|Trade Weighted Growth * Rec|||1.72<br>[.29]***|1.39<br>[.15]***|
|**Underidentification - Weak Identification - Wea**|**k Instruments Tes**|**ts**|||
|LM test statistic for underidentification|||41.87|30.31|
|p-value of underidentification LM statistic (Anderso<br>F statistic for weak identification (Cragg-Donald or|n or Kleibergen-P<br>Kleibergen-Paap)|aap)|9.77e-11<br>21.85|3.68e-08<br>51.14|
|Anderson-Rubin chi-sqared test of significance of e|ndogenous regress|ors|64.05|22.66|
|p-value of Anderson-Rubin chi-sqared test of endog|enous regressors||0|1.20e-05|

Source: Authors’ calculations based on World Economic Outlook database 2019.

Notes: Robust standard errors in brackets. *** p<0.01, ** p<0.05, * p<0.1 Underidentification tests. Ho: matrix of reduced form coefficients has rank=K1-1 -underidentified. Ha: matrix has rank=K1-identified. Weak identification test. Ho: equation is weakly identified. Weak-instrument-robust inference. Tests of joint significance of endogenous regressors B1 in main equation. Ho: B1=0 and overidentifying restrictions are valid.

Table 3 shows the results of running this analysis for our sample of emerging and advanced economies. Column (3) looks at the correlation of public consumption to primary revenue and shows how spending grows at more or less the same rate as revenue (beta estimates are very close
exchange rate returns of both currencies.<sup>21</sup> Ljung-Box statistics for the presence of autocorrelation in the standardized residuals and in the squares of the standardized residuals cannot reject the null at conventional levels.<sup>22</sup>

# **_5.2.1 Mean Equation_**

We first examine the exchange rate mean level. According to our estimates, overall intervention operations during the floating regime have had a highly significant positive impact on the exchange rates, as can be seen from φ _inter_ in Table 4. A net sale of USD 100 million in Mexico appreciates the exchange rate by 0.08 percent, whereas in Turkey a similar operation appreciates the lira by 0.20 percent.

As can be seen from Table 4, the results show that both the size and the frequency of central bank interventions in the market exert a positive pressure on the foreign exchange—i.e. appreciation. More specifically, our findings imply that whenever the exchange market perceives the presence of the central bank, the Mexican peso and the Turkish lira appreciate by 0.12 percent and 0.09 percent, respectively.

> 21 In the case of Mexico, this is in line with Werner (1997a) and Werner (1997b). The difference of local and foreign interest rates was also considered as a regressor; however, this variable became statistically insignificant in both countries once departures from normality are taken into account.

> 22 The exception is net intervention measured in frequencies for Turkey presented in Table 5 where the introduction of qualitative dummies somehow induces heteroskedasticity. To deal with potential model misspecification we calculated robust _t-ratios_ using the Quasi Maximum Likelihood method suggested by Bollerslev and Wooldridge (1992). The results, available from the authors, are consistent with the original findings and basically confirm the conclusions.

19
**<mark>Table 1: Children’s anthropometrics prior to the influx of refugees (refugees Vs. non-refugees receiving areas)</mark>**

||**(1)**<br>**Refugees**<br>**Areas***|**(2)**<br>**Non-refugees**<br>**Areas**|**Overall**|**(1) vs. (2)**|
|---|---|---|---|---|
|**1991**|||||
|Height-for-age Z-score|-1.986|-2.028|-1.991|0.042|
||(0.028)|(0.069)|(0.026)|(0.082)|
|Stunting Prob (HAZ<-2SD)|0.513|0.542|0.516|-0.029|
||(0.009)|(0.024)|(0.008)|(0.026)|
|**1992**|||||
|Height-for-age Z-score|-1.890|-2.017|-1.902|0.127|
||(0.031)|(0.088)|(0.030)|(0.102)|
|Stunting Prob (HAZ<-2SD)|0.489|0.529|0.492|-0.041|
||(0.010)|(0.031)|(0.009)|(0.033)|

**<mark>Source:</mark>** <mark>1991/1992 Tanzania DHS.(*)</mark> Kagera, Kigoma, Geita, Mara, Mwanza and Shinyanga. Standard errors in parentheses.

28
# Table 7: Morality and appropriation

|Equation number|7-1|7-2|7-3|7-4|
|---|---|---|---|---|
|Dep. Var.|Wallets|Firms|Business|Bribe|
||returned|Behave<br>Ethically|costs of<br>crime|Frequency|
|Morality|0.38***|0.55***|0.09|0.49***|
||(3.36)|(5.43)|(0.91)|(5.33)|
|Morality-ability|0.27***|0.12|0.12|0.22***|
|correlation|(2.60)|(1.17)|(1.14)|(2.18)|
|Constant|2.68|2.82|4.31|2.74|
||(10.43)|(12.79)|(17.27)|(11.60)|
|R<sup>2</sup>|.30|.37|.03|.37|
|Mean, dep. var.|4.01|4.27|4.73|4.35|

Dependent variables are from the “Executive Opinion Survey” (World Economic Forum, 2010). Survey questions are printed below. Regression coefficients are standardized. Test statistics (from robust standard errors) are in parentheses. A *,** and *** respectively indicate significance at .10, .05 and .01 levels for two-tailed tests. N = 73.

## 7-1

In your country, if someone loses a purse or wallet containing US$100, and it is found by a neighbor, how likely is it to be returned with the money in it? 1 = Very unlikely, 7 = Very likely

## 7-2

How would you compare the corporate ethics (ethical behaviour in interactions with public officials, politicians and other enterprises) of firms in your country with those of other countries in the world? 1 = Among the worst in the world, 7 = Among the best in the world

## 7-3

To what extent does the incidence of crime and violence impose costs on businesses in your country? 1 = Significant costs, 7 = No costs

## 7-4

In your country, how common is it for firms to make undocumented extra payments or bribes connected with the following:

- a. Imports and exports?  1 = Very common, 7 = Never occurs

- b. Public utilities (e.g. telephone or electricity)?

- c. Annual tax payments?

- d. Awarding of public contracts and licenses?

- e. Obtaining favorable judicial decisions?

42
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19