rafmacalaba/datause-encoder-data huggingface dataset:
**Table A2:** Orthogonality Check: Untargeted vs Targeted

||(1)<br>Untargete|(2)<br>d HHs in...|(3)|(4)|
|---|---|---|---|---|
||Control<br>Clusters|Treated<br>Clusters|Targeted<br>HHs|p-value<br>of F-test|
|_Household Characteristics_|||||
|Household size|3.263|3.354|3.482|0.230|
|Household head is female|0.449|0.466|0.455|0.802|
|Education of head of household (years)|3.122|3.024|2.812|0.590|
|Satisfed with overall house quality (1=Yes)|0.280|0.236|0.270|0.442|
|Satisfed with quality of the house foor (1=Yes)|0.119|0.129|0.085|0.221|
|Satisfed with wall quality (1=Yes)|0.169|0.163|0.177|0.871|
|<br>Satisfed with roof quality (1=Yes)|0.145|0.163|0.169|0.919|
|Satisfed with quality of family life (1=Yes)|0.178|0.209|0.186|0.719|
|Quality of Life Index (ICV)|1.333|1.260|1.307|0.275|
|Hours at home per day|6.576|6.315|6.445|0.927|
|_House Characteristics_|||||
|House with dirt foor (1=Yes)|0.822|0.826|0.847|0.704|
|Number of rooms|2.619|2.472|2.551|0.681|
|Share of bedrooms with dirt foor|0.713|0.715|0.754|0.598|
|<br>Walls made of wood or zinc (1=Yes)|0.559|0.551|0.536|0.887|
|House is owned (1=Yes)|0.932|0.944|0.959|0.687|
|Monthly rent if leased out (USD)|85.037|41.478|65.071|0.118|
|<br>Most important repair was not foor upgrade(1=Yes)|0.441|0.472|0.430|0.597|
|Number of households|118|178|740|1036|

Notes: See Appendix Table A1 for variable definitions. Columns 1-3 report means while column 4 reports the p-value of an F-test that means across groups in columns 1-3 are jointly different from zero. Municipality fixed effects are included. SE are clustered at the cluster level. (*** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1).

23
EU-Chile PTA of 2003).<sup>4</sup> These distinct approaches could affect the fixed costs of exporting for firms in different ways. Mutual recognition of member countries’ regulations is expected to reduce the fixed costs for firms from having to comply with a multiplicity of regulations (Baldwin, 2000). Firms only need to comply with their domestic regulation to have their products accepted in PTA partners’ markets. The harmonization of member countries’ regulations may initially increase the fixed costs of exporting for firms as they need to cope with the newly established standards. Then the use of a common standard (especially if it is an international standard) may increase the size of the market allowing firms to exploit economies of scale.<sup>5</sup> But evidence on the impacts of including SPS and TBT provisions in PTAs on firm export performance is lacking. Do the SPS and TBT regulations incorporated in PTAs benefit small firms or are benefits mitigated since large firms influence the design of PTAs as suggested by Rodrik (2018)? Do mutual recognition and harmonization of PTA member countries’ regulations have a heterogeneous impact across firms?

This paper addresses these questions by investigating the impact of PTAs regulating SPS and TBT on firms along the size spectrum combining two main novel sources of data. The first source of data we exploit is the World Bank’s Deep Trade Agreements database of Mattoo et al. (2020) that contains all provisions related to the policy areas of SPS and TBT (as well as many other policy areas) included in PTAs signed over the last 40 years. We combine this data with longitudinal administrative firm-level databases from customs in Chile, Colombia, and Peru covering the universe of exporters between 1996 and 2015 part of the Exporter Dynamics Database described in Fernandes et al. (2016). These three countries share many similarities in their economic and trade structures and constitute an excellent laboratory for studying the impacts of PTAs as they were signatories to close to 40 new PTAs with a variety of trading partners that entered into force during the sample period.

Our empirical strategy isolates the change in firm export performance driven by the regula-

> 4Common standards within a PTA can be existing international standards (e.g., the Codex Alimentarius Committee standards for food safety) or new regional standards developed by the PTA members.

> 5Schmidt and Steingress (2019) argue that an expected benefit from harmonization is higher demand if harmonized rules are based on consumer preferences and on compatibility between products across countries.

2
# **Economic and Distributional Impacts of Selected Carbon Pricing Policies for the Arab Republic of Egypt**

# **1. Introduction**

The Arab Republic of Egypt is the 24<sup>th</sup> largest CO2 emitter from fossil fuel combustion in the world and the third largest emitter in the MENA region after the Islamic Republic of Iran (7<sup>th</sup> largest) and Saudi Arabia (11<sup>th</sup> largest) (World Bank, 2022a). Total greenhouse gas (GHG) emissions in 2019 were 1.6 times as high as in 1990; and per capita emissions increased by 47% during over 1990–2019 (World Bank, 2022b). The country is highly vulnerable to climate change due to increased water scarcity, loss of biodiversity and food insecurity (World Bank, 2022). Considering the growth of GHG emissions, its vulnerability to climate change,<sup>2</sup> and realizing the global responsibility to address climate change, Egypt has actively participated in international efforts to combat climate change. Egypt ratified the United Nations Framework Convention on Climate Change (UNFCCC) in 1994. Under the Paris Climate Agreement, Egypt has set a target of reducing one-third (33%) of its emissions in the baseline in 2030 (Government of Egypt, 2022). As indicated in its Nationally Determined Contribution (NDC), the emission mitigation target will be achieved through various measures, such as removing fossil fuel subsidies, promoting renewable energy, improving energy efficiency, and transitioning to low-carbon transportation. Egypt’s commitment to contribute to global efforts to address climate change is also reflected in its hosting of the 27<sup>th</sup> Conference of the Parties (COP) to the UNFCCC in November 2022. Despite Egypt’s target of reducing 33% of its GHG emissions as specified in its NDC, an acute knowledge gap exists on how meeting the NDC target will affect the overall economy and how these impacts will be distributed across households.

Carbon pricing instruments, such as a carbon tax, are the main pricing instruments considered by many countries to reduce their GHG emissions because they are economically

> 2  According to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), the Nile Delta is one of the three extreme vulnerable hotspots mega-deltas directly affected by 2050 (Nicholls et al. 2007). The timing and volume of Nile River water availability to Egypt is increasingly uncertain due to climate change impacts (World Bank, 2022b).
Table 1. Descriptive Statistics

||P|EP Ineligible|||PEP Eligible||
|---|---|---|---|---|---|---|
|_Panel A:_Control Variables(baseline)|N|Mean|SD|N|Mean|SD|
|Age (years)|596|32.50|8.517|750|35.79|9.349|
|Number of children|596|1.661|1.426|750|1.479|1.508|
|Household Venezuela: parents or siblings [=1]|596|0.465|0.499|750|0.424|0.495|
|Household Venezuela: partner/spouse [=1]|596|0.539|0.499|750|0.564|0.496|
|Household Venezuela: others [=1]|596|0.129|0.336|750|0.0853|0.280|
|Knew of job opportunity before migrating [=1]|596|0.354|0.479|750|0.341|0.474|
|Ever worked [=1]|596|0.971|0.167|750|0.980|0.140|
|Employed at private frm [=1]|596|0.602|0.490|750|0.612|0.488|
|Employed with Government [=1]|596|0.148|0.355|750|0.153|0.361|
|Self-employed or employer [=1]|596|0.174|0.380|750|0.180|0.384|
|Written contract [=1]|596|0.451|0.498|750|0.563|0.496|
|Gap between last job and migration (months)|596|0.876|3.710|750|1.311|5.038|
|Years of education before migration|596|12.95|2.923|750|13.55|2.696|
|Migrated for health reasons|596|0.102|0.303|750|0.101|0.302|
|Friends/family in Colombia|596|0.773|0.419|750|0.700|0.459|
|Time in Colombia (months)|584|49.53|7.984|736|56.09|11.59|
|Had smartphone [=1]|596|0.492|0.500|750|0.648|0.478|
|Owner of dwelling in Venezuela [=1]|596|0.866|0.341|750|0.864|0.343|
|Electricity in Venezuela [=1]|596|0.995|0.0708|750|0.993|0.0814|
|Running water in Venezuela [=1]|596|0.837|0.369|750|0.875|0.331|
|Sewage in Venezuela[=1]|596|0.940|0.238|750|0.931|0.254|
|_Panel B:_Outcomes(All waves)|||||||
|Likelihood of having children of 0 years of age|2,538|0.0402|0.196|1,500|0.0447|0.207|
|<br>Likelihood of having children of 1 years of age|2,538|0.0587|0.235|1,500|0.0447|0.207|
|Likelihood of having children of 2 years of age|2,538|0.0248|0.156|1,500|0.0200|0.140|
|<br>Likelihood of havingchildren of 3years of age|2,538|0.00158|0.0397|1,500|0.000667|0.0258|

_Notes:_ The table presents descriptive statistics for the households in our sample (596 ineligibles and 750 eligibles = 1,346 households). Panels A and B show the head of household’s characteristics measure before the migration episode and the main outcome measures for all waves, respectively.

24
# **Table 2: New migrants to and natives of developed countries tend experience the greatest gains to real income from higher South-North migration flows** <u>Difference from baseline of real income in 2030 (US$ Billions)</u>

|||**Incu**<br>**Mig**<br>|**mbent**<br>**rants**<br>|**Na**|**tives**<br>|
|---|---|---|---|---|---|
||**New**<br>**Migrants**|**from**<br>**LMIs**|**from**<br>**HICs**|**Host**<br>**Region**|**Origin**<br>**Region**|
|Australia, New Zealand, and Other||||||
|Oceania|4.61|-2.85|2.36|15.07||
|Canada|5.35|-3.15|1.60|18.72||
|European Economic Area|53.64|-32.51|9.55|189.29||
|High-Income Asia|19.29|-10.45|0.30|51.91||
|High-Income Middle East|2.56|2.20|1.60|16.25||
|Russian Federation|4.45|-2.09|0.13|16.91||
|USA|103.95|-44.12|3.76|146.09||
|Bangladesh||0.01|0.00||23.66|
|Brazil||0.00|-0.01||2.72|
|Central Asia||-0.18|-0.46||0.41|
|China||0.00|0.00||0.61|
|India||0.02|0.02||29.54|
|Indonesia||0.00|0.00||5.20|
|Low-Income Sub-Saharan Africa||0.03|0.05||8.24|
|Mexico||-0.01|-0.22||11.19|
|Middle-Income Middle East and North<br>Africa||0.01|0.11||21.49|
|Other Former Soviet Union and Other||||||
|Eastern Europe||-0.27|-1.79||1.75|
|Other Latin America and the Caribbean||-0.24|-0.27||16.07|
|Other Low-Income South and East Asia||0.01|0.01||4.37|
|Other Middle-Income Asia||-0.02|0.09||5.39|
|Other Middle-Income Sub-Saharan||||||
|Africa||0.05|0.14||1.06|
|Pakistan||0.00|0.00||4.54|
|South Africa||-0.03|-0.03||5.08|
|Turkey||-0.03|-0.58||-5.55|
|**Total**|**193.840**|**-93.607**|**16.353**|**454.249**|**135.748**|

Note: The decomposition assumes that new migrants earned only labor income and received no remittances in the baseline and that the incumbent migrants receive a share of the host region’s non-labor income that equals their respective shares in labor income. New migrants’ real income change is the after-tax CPI-deflated labor income net of remittance transfers adjusted for purchasing power differentials between the host and the origin region minus CPI-deflated baseline net labor income. For the other groups, the figures are the sum of changes in their CPIdeflated net factor income and remittances sent or received 19
## **Estimating wage impacts of food price changes**

In order to link changes in food prices with the resulting changes in wage rates for unskilled workers, we use the assumptions, parameters and data of the GTAP model to replicate the GTAP-style nested CES production relationships at a national level with all prices kept exogenous. Following the standard GTAP model, we model output as a combination of inputs and value-added in the top nest, and value-added as a combination of factors in the bottom nest. Finally, we impose zero profit conditions at each nest and restrict the total quantity of factors available to each country.

To calculate the implications of the changes in output prices and wage rates on labor demand and outputs, we express the model equations in their log-linear form as: [Me|Mx] �x<sup>x</sup> x<sup>e�=</sup> [0] where �x<sup>x</sup> x<sup>e� is a stacked vector of endogenous xe and exogenous variables xx and [Me|Mx] is</sup> a matrix of coefficients of the equations with block Me corresponding to the endogenous variables and block Mx corresponding to the exogenous variables. By solving this equation, we obtain log-linear reduced-form relationships between all exogenous variables (output prices) and endogenous variables (wages etc.) as xe = ρxx where ρ= −Me−1Mx is the elasticity matrix.

Because we are interested in medium- and long-run wage elasticities, we calculate ρ under two sets of assumptions. For the medium run, we assume a specific-factors model where capital, land and natural resources are fixed and labor is the only mobile factor. For the long-run scenario, we assume that both labor and capital are fully mobile and land is sluggishly adjustable, with an elasticity of transformation equal to one, as assumed in the GTAP model. We report the calculated sets of Stolper-Samuelson elasticities of unskilled wage rates with respect to output prices in Appendix tables 1 and 2.

# **Implementing the Approach**

Ideally one would analyze the impacts of shocks such as food price changes on household incomes using a model in which demands for goods were determined as the total of demands from individual households, and supplies were similarly determined using models of individual producing firms. Unfortunately, the development of such a model for our purpose is very challenging at this point given the incomplete coverage of household surveys and differences in 8
27 1991) and a comparison of actuals with projected values is not possible. Comoros is also dropped because it has only one PFP until November 1992, cut-off point of this exercise. According to the latest available data, the overall progress on reduction of budget deficit as a ratio of GDP is rather slow in all those CD3 countries. Zaire's budget deficit ratio has been consistently high and in one );ar (1988) the actual figure was 10 percentage points higher than what was projected. Burundi's budget deficit also exceeded projected values by a substantial margin in some years. Madagascar's performance on budget deficit is slightly better - budget deficit to GDP ratio declined in 1990, contrary to what was projected. In 1991, the situation changed and Madagascar's budget deficit went up contrary **to** what was projected. Since 1990, Madagascar's current account to GDP ratio was better than projected.

The record with regard to investment and savings rate has been mixed. Actual gross investment to GDP ratio for Burundi for the years 1988 to 1991 were lower than projected value, although the gap somewhat narrowed in recent years. Madagascar has experienced widening discrepancies between acthla and projected values since 1987. For the four countries, the average investment to GDP ratio has been 4 to 5 percent lower than what was projected. As for savings to GDP ratio, the projected values have proved to be generlly ambitious. For Burundi, PFPs projected that savings to GDP rates would be on average _5_ percent, whereas the actual rate on average was less than one percent. for Madagascar, the projected rate on average is also 3 percent higher than the actual outcomes. For Zaire, the projected savings rate turned out to be similar to what were projected.
Policy ReseaRch WoRking PaPeR 4435

# **Abstract**

This paper tests the hypothesis that enterprises may forgo formal finance in lieu of informal credit by choice. They do so to avoid the additional regulatory scrutiny and harassment that engaging with the formal financial sector invites. We test this hypothesis using enterpriselevel data on 3,564 enterprises in 29 countries. In this sample, enterprises finance approximately 57 percent of their working capital requirements with external finance. This external finance comes from formal sources, such as commercial banks (53 percent) and informal sources (42 percent), such as trade creditors, or family and friends. In our sample, 14 percent of enterprises rely exclusively on informal finance. We find that the likelihood of enterprises preferring to only use informal finance is inversely related to the quality of the regulatory environment, particularly the quality of tax administration and overall governance. For example, we find that when an enterprise has been asked for bribes by tax inspectors, it is 17 percent more likely to prefer informal finance.

This paper—a product of the Enterprise Analysis Unit in the Financial and Private Sector Development Vice Presidency—is part of a larger effort in the department to better understand how the legal and regulatory environment affects financial access. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at msafavian@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
# Preface

Many developing countries face heavy pressures and demanAs for expanding educational opportunities in higher education. Often, the response resulted in accelerated quantitative growth and qualitative decline. Higher education also claims a substantial portion of educational budgets and the priorities of governments have been a subject of controversy. In light of this, and as part of its work program, the Education and Employment Division of the Population and Human Resources Department of the World Bank has initiated regional and country case studies on higher education with a view to assessing issues of efficiency, relevance, and finance.

This paper is a study of the status of universities in the Arab countries of the Middle East and North Africa. Its major objectives are: (a) To provide a general overview of the status of universities in the Atab countries of the Middle East and North Africa; and (b) To highlight i0sues and problems in higher education faced by universities. The study is restricted to universities granting the bachelor's degree or higher and excludes polytechnic institutes and community colleges. It does not include non-Arab Middle Eastern countries like Iran and Turkey nor does it include Arab countries categorized in the Africa Region of the World Bank. Specifically, the following countries are covered Algeria, Egypt, Libya, Morocco, Tunisia, Bahrain, Yemen Arab Republic, Peopls's Democratic Republic of Yemen, Iraq, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Syria, and the United Arab Emirates.

The report consists of the following three sections: I. An overview of the status of universities in the Arab countries of the Middle East and North Africa. This is an extensive overview that starts with an introductory background and includes subsections dealing with governance, structure, admission and enrollment, financial resources, curricula and methods of instruction, foreign exposure, and women's education. Annex I provides information on '7s. iniversities in the countries under considerat d Annex 2 gives percentages of foreign stut different host countries.

II. A list of higher education issues and problems faced by universities.

III. Concluding remarks.

Valuable comments and views were provided by Messrs. W. Haddad, R. Ilarbison, and J. Schweitzer and I am grateful to them.

_(i)_
Table 9: Long-term Effect of FPE on Educational Achievement: DR DID estimates

|VARIABLES|(1)<br>|(2)<br>|
|---|---|---|
||Treatment group:<br>First year students|Treatment group:<br>16-18 year olds|
|Panel A: Traditio<br>|nal DR DID estimates||
|ATT (<sup>ˆ</sup>_δDRDID_)|2.8628***<br>(0.8439)<br>[1.1369, 4.5888]|0.7666<br>(0.5148)<br>[-0.3085, 1.8416]|
|Observations|14,095|14,095|
|Panel B: Improve|d DR DID estimates||
|ATT (<sup>ˆ</sup>_δDRDID_)|5.7425***<br>(0.8318)<br>[1.4052, 10.0798]||
|Observations|14,095||

_Notes_ : The point estimates of the FPE effect on achievement (OWM) and standard errors in parentheses are produced using `DRDID` R code by Sant’Anna and Zhao (2020). Bootstrapped standard errors with 1000 replications are in parentheses. 95% Confidence intervals in brackets. Significance levels are indicated as follows: *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1. The covariates used in the estimation of the propensity score are APS, gender, district, and age (age dummies in the first column to approximate the cohort effects, and age and age squared in the second column). Panel A reports traditional DR DID estimates that are DR consistent and locally semiparametrically efficient. Panel B reports DR DID estimates that are DR consistent, locally semiparametrically efficient, and DR efficient (i.e. they are efficient under misspecification in either the outcome model or the propensity score).

# **6.4 Potential mechanisms**

So far, I have not specified any possible channels through which FPE program generates these positive effects. This section attempts to narrow down on the possible causal channels through which the observed positive effects the program could have emerged based on figure 4 and previous research.

It is well documented in the literature that elimination of user-fees leads to an increase in access to schooling and, conditional on teacher recruitment, increases pupil teacher ratio (PTR) (see Grogan, 2009; Chyi and Zhou, 2014; Moshoeshoe _et al._ , 2019). And high PTR, especially due to an influx of poor children coming to school, leads to a decline, or at the most no change, in academic performance, holding all else constant (see Case and Deaton, 1999; Lucas and Mbiti, 2012). Similarly, building more schools, holding teacher recruitment constant, leads to an increase in access and PTR, and hence a decrease in academic achievement.

Furthermore, conditional on enrollment and teacher quality, increasing access to textbooks leads to an increase, at least not a decline, in academic achievement (see Glewwe _et al._ , 2009; 31