rafmacalaba/data-use-mentions-extended huggingface dataset:
STEVEN PENNINGS 2 <!-- Start of picture text --> A. Pass−through of Bilateral RER to US Import Prices B. Pass−through of Competitors’ RER to US Import Prices<br>Imports from Canada, Euro Area, Japan (1990−2013) Imports from Canada, Euro Area, Japan (1990−2013)<br>Slope=0.32<br>Slope=0.23<br>−.2 −.1 0 .1 .2 −.2 −.1 0 .1 .2<br>Bilateral RER (annual change log) Competitors’ RER (annual change log)<br>Sources: FRED and BLS. See Appendix for details. Note: Comp RER is Real Broad TWI excl. bilateral RER. Sources: FRED, BLS. See Appendix.<br>.05 .05<br>0 0<br>−.05 −.05<br>Real Import Price (annual change log) Real Import Price (annual change log)<br>−.1 −.1<br><!-- End of picture text --> Figure 1. Aggregate-level pass-through of bilateral and competitors’ RERs to US import prices sizable pass-through of the trade weighted index (TWI) exchange rate to import prices as discussed briefly in GI2011. Pass-through of competitors’ RERs to US producer prices is around 0.1 in the BLS microdata.<sup>2</sup>

**Model** To compare the quantitative size of these forces in theory and data, I develop a multi-country extension of AB where (i) goods are more substitutable within than between sectors, and (ii) the small number of firms in each sector engage in Cournot competition. A linearized version of the firm’s pricing equation has the same form as the general class of models discussed above: firms respond to competitors’ prices. Solving for those prices generates a linear “structural pass-through
imperfection - leads to more reliance on non-financial inflation hedges as investment in real estate and gold that are perfect substitutes of financial savings.

Short-term influence of real interest rates and financial development on real private savings are in line with theory and our earlier interpretation of long-term equation. Both variables are positively related to real private savings in the short term. This is in full conformity with the LCH.

Market openness has a significant effect on private savings. Exchange rate movement in the previous period reflects on real private savings in the current period. This is consistent with the analysis on the impact of short-term inflation. In general, devaluation of domestic currency in LDCs with limited capital mobility raises the public aversion to future uncertainties and trigger higher precautionary savings to mitigate future macroeconomic shocks. Another interpretation for the case of LDCs is that devaluation inflates the volume of the equivalence of foreign currency deposits in domestic currency. This has in turn led to a positive net effect for exchange rate devaluation on real private savings. Furthermore, the rise of foreign exchange rate triggers dissavings and preference to store of value in non-financial assets (See Hussein and Mohieldin 1997).

# **Conclusion**

A mix of the simple permanent income hypothesis as well as the life cycle hypothesis determinants are used to interpret real private savings behavior in Egypt. This study provides new empirical evidence related to savings behavior, financial development, and economic growth in Egypt. By using high quality and high frequency quarterly data covering 1991-2010, this study employed a robust vector equilibrium correction modeling strategy. The key long-term determinants of private savings in Egypt are the real interest rate and level of financial development. The data also show higher persistence of real private savings in the short run.

The real interest rate varies negatively with real private savings in the long term for the period under consideration, 1991 – 2010. This translates to the fact higher consumption is becoming more attainable at lower cost. Hussein and Mohieldin (1997) reached the same conclusion on the relation between private savings and real interest
parameter is particularly relevant to determine the e¤ect of immigrants on wages of natives and, as we will see, the choice of this parameter makes some di¤erence in evaluating the e¤ects of migration in certain countries. Borjas et al (2008) and Ottaviano and Peri (forthcoming) use US data and Manacorda et al (forthcoming) use UK data in their estimation.

Finally the parameter �, whose magnitude has been estimated using data from US cities (Moretti 2004a, 2004b) or US states (Acemoglu and Angrist 2000 and Iranzo and Peri 2009) is also subject to a certain level of disagreement between those who ...nd substantial schooling externalities and those who do not.

To preview the main features of the dependence of the simulated e¤ects on parameter values, �q has very little bearing on the impact of immigration and emigration on average wages, but it is critical for the e¤ects on the wage distribution between more and less educated natives. The parameter �I in‡uences the average wage impact of immigration on natives but has no bearings on the impact of emigration. Finally � matters for the impact of immigration and emigration on average wages with no e¤ect on the wage distribution.

## 4.2 Simulation with the basic speci...cation

Table 3 and the three panels of Figure 1 show the long-run impact of immigration (dotted line), emigration (dashed line)) and net migration (solid line) between 1990-2000 on average

> 11Those preference parameters play a minor role in our wage simulations. They enter both the numerator and denominator in the expressions for percentage changes in wages and hence they canel out.

12
_Access to improved drinking water sources_ . Figure 2 shows that access to improved drinking water also rose notably across all three countries during this period. In Ghana and Nigeria, access at the MV intervention site rose more quickly than the surrounding area, but areas outside the intervention site also experienced substantial gains. (Again, MVP 2010c does not report this statistic for the MV in Kenya.) _Measles immunization_ . The fraction of children immunized against measles rose in all three countries during the period (Figure 3). In Ghana, vaccination rates rose at the MV intervention site less than in the surrounding area. In Kenya and Nigeria, vaccination rates rose at the MV intervention site more than they rose in the surrounding area.

_Births delivered by skilled personnel_ . Figure 4 shows that the fraction of live births in the previous 2 years delivered by a doctor, nurse, or community health worker rose in Kenya and Ghana, while showing little change in Nigeria. At the MV intervention site in Kenya, skilled birth attendance fell while it was rising in the surrounding region. In Ghana, skilled birth attendance rose at the MV site more than in the surrounding region. In Nigeria, it increased only slightly at the MV intervention site relative to the surrounding area, despite the construction of a new, doctor-staffed, $174,000 clinic within Pampaida locality (Boyd et al. 2009).

_HIV testing_ . Figure 5 shows that HIV testing rates rose greatly across Kenya and Ghana during this period and fell in Nigeria. In Kenya and Ghana, HIV testing at the MV intervention sites rose more than in the surrounding areas. In Nigeria, HIV testing at the MV site rose while falling in the surrounding area. Kenya faces a major HIV epidemic while HIV is present but much less prevalent in Ghana and Nigeria.

_Bednet usage_ . Figure 6 reveals that insecticide-treated bednet usage by small children increased enormously across Kenya and Ghana and by a small amount across Nigeria during the period. At the MV intervention sites in Kenya and Ghana, bednet
sup>�</sup><br>_X_<sup>_k_</sup><br>_jt_<sup>)</sup>|0.789***|0.802***|0.801***|0.800***|0.825***|
|_,_|(0.0258)|(0.0321)|(0.0322)|(0.0306)|(0.0340)|
|Observations|5,892,852|5,892,852|5,892,852|5,892,852|5,892,852|
|Year FE|YES|YES|YES|YES|YES|
|Flexible distance controls|NO|NO|NO|YES|YES|
|U.S. trade policy controls|NO|NO|NO|NO|YES|
|Pseudo R2|0.420|0.443|0.446|0.453|0.500|

Note: Robust standard errors in parentheses. *** p _<_ 0.01, ** p _<_ 0.05, * p _<_ 0.1. The LHS variable on all models is _M_<sup>_k_of</sup> _j,t_<sup>, the total value imported in Puerto Rico from place of origin</sup><sup>_j_</sup> product _k_ in year _t_ . All models are estimated using the PPML estimator on Puerto Rico’s import data pooled across observations at the year, HS6 digit product, and place-of-origin level, with year fixed effects included in the estimation model. Pharmaceutical products are excluded from the estimation. IHST denotes the Inverse Hyperbolic Sine Transformation.

35
continued to be based on crude aggregates of around 25 products chosen for tractability and consistency with production and consumption data that are generally available only at much higher degrees of aggregation. In this study, we use the broad approach to aggregation developed by Bach and Martin (2001) to deal with the problem of aggregation when protection rates vary substantially within the groups used in the analysis. Under this approach, we form distinct aggregates for both expenditure on goods, and for tariff revenues, distinguishing, following Anderson (2009), between quantity aggregates at domestic and international prices.

Before applying the approach, we first consider its implications using a simple, graphical approach. We show that the use of optimal aggregators has two important implications. Within each aggregate group used, the marginal impact of a tariff reduction on expenditures will be greater than its marginal impact on tariff revenues, since each reduction in tariffs increases the volume of imports on which tariffs are collected. This difference allows us to capture true welfare gains that are omitted when using traditional trade-weighted averages, and which decline as liberalization proceeds. However, as tariffs decline, rising weights on tariffs that have experienced large tariff reductions increase the weights on reductions in these tariffs. This qualitative analysis raises a question that we address in the analysis—of whether optimal aggregators have a larger impact when considering complete tariff liberalization, or in the initial stages of liberalization.

To provide an answer to the questions posed, we apply the technique, using detailed tariff information provided by the MAcMapHS6v2.1 database, in a modified version of the LINKAGE global general equilibrium model, taking into account the nested structure of import demand in that model. Using this aggregation procedure with a conservative estimate of the elasticity of substitution between six-digit tariff lines results in a substantial increase— close to a doubling—in the estimated welfare gains from complete liberalization of global trade barriers both for aggregate country groups and for most individual countries. The impact is not the same across countries, with some of the exceptions providing very important
**<u>Table 3: Transition matrices by major crop types for 2017 and 2018</u> Panel A: 2016/17**

||||2017<br>|||
|---|---|---|---|---|---|
|2016|Sunflower|Maize|Cereals|Soybean|Total|
|Sunflower|2.29|1.14|3.71|0.64|7.78|
|Maize|2.21|2.38|0.79|1.06|6.44|
|Cereals|6.01|1.74|2.56|0.65|10.95|
|Soybean|0.42|0.83|0.69|0.67|2.62|
|Total|10.93|6.09|7.76|3.02|27.79|
|**Panel B: 2017**<br>|**/18**<br>||2018<br>|||
|2017|Sunflower|Maize|Cereals|Soybean|Total|
|Sunflower|1.78|1.80|5.05|0.77|9.41|
|Maize|2.35|2.36|1.00|1.34|7.05|
|Cereals|5.18|1.26|2.58|0.83|9.84|
|Soybean|0.48|0.74|0.63|0.65|2.50|
|Total|9.79|6.15|9.26|3.59|28.79|

_Source:_ Own computation based on remote sensing-based crop classification as described in text.

17
# **Rising Food Prices and Household Welfare: Evidence from Brazil in 2008**

Francisco H. G. Ferreira, Anna Fruttero, Phillippe Leite, and Leonardo Lucchetti<sup>1</sup> September 27, 2011

**Keywords:** Food prices, welfare, poverty, inequality, price change incidence curve, Brazil. **JEL Codes: D31, I38, O15**

**Abstract:** Food price inflation in Brazil in the twelve months to June 2008 was 18 percent, while overall inflation was seven percent. Using spatially disaggregated monthly data on consumer prices and two different household surveys, we estimate the welfare consequences of these food price increases, and their distribution across households. Because Brazil is a large food producer, with a predominantly wage-earning agricultural labor force, our estimates include general equilibrium effects on market and transfer incomes, as well as the standard estimates of changes in consumer surplus. While the expenditure (or consumer surplus) effects were large, negative and markedly regressive everywhere, the market income effect was positive and progressive, particularly in rural areas. Because of this effect on the rural poor, and of the partial protection afforded by increases in two large social assistance benefits, the overall impact of higher food prices in Brazil was U-shaped, with middle-income groups suffering larger proportional losses than the very poor. Nevertheless, since Brazil is 80 percent urban, higher food prices still led to a greater incidence and depth of poverty at the national level.

> 1 Ferreira, Fruttero, and Leite are with the World Bank. Lucchetti is at the University of Illinois at UrbanaChampaign. We are grateful to Ricardo Paes de Barros, Tito Cordella, Ambar Narayan, Helena Ribe, and seminar participants at Georgetown University, the World Bank, the 31<sup>st</sup> Annual Meetings of the Brazilian Econometric Society, the 4<sup>th</sup> ECINEQ Meetings in Catania (Italy) and the IAMO Forum 2011 in Halle (Germany)
|**Contribution Country**|**Liberia**|**Ethiopia**|**Rwanda**|**Nigeria**|**Zambia**|
|---|---|---|---|---|---|
|Localjob creation?|√|√|√|√|√|
|Local industrialization?|X|√|√|√|X|
|Technology transfer?|X|X|X|X|X|
|Overall|n/a|√|√|√|√|

_Source: Shen and Zai._ Several host countries provided specific data on jobs generated by Chinese investment projects. In Nigeria, 600 or so Chinese businesses generated approximately 69,000 jobs by 2011; in Ethiopia, 290 Chinese firms provided 35,000 regular jobs and nearly 40,000 seasonal jobs by the same time. In Liberia and Rwanda, where employment data are also available, over 3,000 jobs were reported in each case.

Responding host governments also gave their specific concerns regarding Chinese investment. As seen in Table 2, there are a number of concerns shared by host countries, with “increased competition hurting local industries” at the top. “Poor labor standards” are also commonly mentioned. Further, three out of the five countries found it difficult to communicate with Chinese firms due to “language and cultural barriers.” Finally, two countries expressed concerns about “poor environment standards” and one expressed concerns about “immigration.”

**Table 2: Concerns of African Governments about Chinese Investment**

|**Concern Country**|**Liberia**|**Ethiopia**|**Rwanda**|**Nigeria**|**Zambia**|
|---|---|---|---|---|---|
|*
859|0.146|0.216|0.615|0.235|
|P-val of B = NB in L villages|_0.005_|_0.033_|_0.000_|_0.396_|_0.000_|

Note: This table reports the estimation of the following specification: _y ij = α ij + β 1 Beneficiary ij + β 2 Lottery j + β 3 Lottery j *Beneficiary ij + ε ij_ , where _i_ indexes the individual (household) and _j_ indexes the village. _Beneficiary ij_ is a dummy that takes value of 1 if the individual _i_ in village _j_ is a beneficiary of the NAIVS voucher program in 2010/11. _Lottery j_ is a dummy that takes value of 1 if beneficiaries in village _j_ were chosen using a lottery. The models presented here represent an intention to treat analysis and are not adjusted for any baseline covariates. Dependent variables are constructed based on questions asked on follow-up household survey. The dependent variable in Column 1 is a dummy that indicates whether respondent is aware of the presence of the NAIVS program in his or her village. Column 2 reports the results using a dummy that codes whether the respondent was asked about his or her ability to pay for the voucher top-up in 2010/11. In Columns 3 and 5, the dependent variables are dummies that indicate if respondent reports receiving vouchers in 2010/11 and 2011/12, respectively. For those regressions, respondents self-report receiving or not voucher and the answers may differ from administrative data used to assign beneficiary status. In Column 4, the dependent variable is a dummy variable that indicates whether the respondent reports being very satisfied with the selection of voucher beneficiaries in 2010/11. P-values are computed using the t-asymptotic wild cluster bootstrap procedure described in Cameron et al. (2008) and reported below the coefficients. Clustering was done at the village level. ***,**,* denote statistical significance at the 1, 5 and 10 percent level, respectively. See
Sequeira, S. (2011). ―Transport Costs and Firm Behavior,‖ in Cadot, O., Fernandes, A., Gourdon, J., and A. Mattoo (eds.) _Where to Spend the Next Million? Applying Impact Evaluation to Trade Assistance,_ pp. 123-162. The World Bank and CEPR.

Tan, H. (2009). ―Evaluating SME Support Programs in Chile using Panel Firm Data,‖ World Bank Policy Research Working Paper 5082.

Todd, P. (2008). ―Evaluating Social Programs with Endogenous Program Placement and Self Selection of the Treated,‖ in Schultz, T.P. and J. Strauss (eds.) _Handbook of Development Economics_ , vol. 4, pp. 3848-3894.

Volpe, C. and J. Carballo (2010). ―Beyond the Average Effects: The Distributional Impacts of Export Promotion Programs in Developing Countries,‖ _Journal of Development Economics_ 92, 201-214.

Volpe, C. (2011). ―Assessing the Impacts of Trade Promotion Interventions: Where Do We Stand?,‖ in Cadot, O., Fernandes, A., Gourdon, J., and A. Mattoo (eds.) _Where to Spend the Next Million? Applying Impact Evaluation to Trade Assistance,_ pp. 39-80. The World Bank and CEPR.

Wagner, D. (2003). ―Aid and Trade - an Empirical Study,‖ _Journal of the Japanese and International Economies_ 17, 153-173.

WTO (2009). _World Trade Report 2009: Trade Policy Commitments and Contingency Measures_ . Geneva: World Trade Organization.

World Bank (2009). _Unlocking Global Opportunities: The Aid For Trade Program of the World Bank Group_ . Washington, DC: The World Bank.

World Bank (2011). ―Leveraging Trade for Development and Growth: The World Bank Group Trade Strategy, 2011-2021,‖ Washington, DC: The World Bank.

43
Finally, the study does not cover customary or religious law because of their often-uncodified status and the resulting difficulties in defining their rules.

The survey data are current as of December 31, 2015. If a law was enacted but did not come into force before that date, the law was not included in the country data. Nonetheless, it was mentioned in the paper.

# V. Findings and Analysis

The main goal of this paper is twofold: (a) to test six new indicators and the methodology for the collection of crosscountry comparable data on discriminatory legal frameworks related to ethnic, religious, and sexual minorities; and (b) to present some findings from the data collection in six economies, highlighting some good and bad practices in the legal frameworks as they relate to equality of opportunities for minorities and their access to institutions, education, property, the labor force, social services, and protection from hate speech and hate crimes (the indicators). In doing so, the study aims to fill a gap in the existing literature related to poverty and development, which seldom looks at the issue of discrimination against those minorities through the prism of the effect that such exclusion might have on their economic potential and the overall cost for the country.

Following is an overview of the data collected (a) in the six pilot countries through the three surveys distributed to local experts and (b) from international legal databases and human rights organizations. The results are divided by indicators. Details of the specific variables examined and the answers to the surveys may be found in appendix C.

# _1. Access to Institutions_

The access to institutions indicator explores the ability of individuals within a minority group to interact and influence the decision-making process of public authorities in the same way as people belonging to the majority or ruling minority. The indicator also covers certain fundamental political rights, such as the freedom of expression and freedom of religion. Participation of minorities in all three branches of government—legislative, executive, and judiciary—is a
MPI, constructed in Admasu et al. (2021), to capture the deprivations of forcibly displaced individuals and their gendered lives.

The paper proceeds as follows. Section 2 reviews the existing literature to provide the background and motivation for the analysis, including a summary of the different country contexts covered by the case studies in this paper. Section 3 outlines the measurement strategy for deconstructing the MPI used for analysis and its limitations, followed by Section 4, which introduces the data. Section 5 presents the findings, first for deprivation results at the individual level and then results evaluating intrahousehold inequalities. Concluding remarks are discussed in Section 6.

# **2 Background and Literature Review**

# **_2.1 Individual-level measures of gender and multidimensional poverty_**

Individual-level analyses of multidimensional poverty have mostly centered around children, with various studies analyzing the relevance of indicators for children (aged 0- 17 years),<sup>2</sup> as well as other age ranges. The MPI has also been used to better understand gender issues, for example, Batana (2008) implemented a women’s MPI in Sub-Saharan Africa. Bhutan’s Gross National Happiness measures (2010, 2015), Vijaya et al. (2014), and Klasen and Lahoti (2016) are implemented at the individual level. The Women’s Empowerment in Agriculture Index (WEAI) (Alkire et al. 2012) uses individual-level data, and the linked Gender Parity Index reflects inequalities across women and men’s deprivation scores within the same household. Alkire, Apablaza and Jung (2014) design and implement an exploratory individual-level MPI for 31 European countries over six waves of data using EU-SILC data sets, finding no cases in which are women significantly less poor than men, and in many cases, they are significantly poorer. Espinoza-Delgado and Klasen (2018) create an individual-level MPI to understand differences in poverty between women and men in Nicaragua, finding similar overall incidence, but much higher intensity of poverty among women.
product falls into category (2) and zero otherwise. Of the 3542 products exported over the sample period, more than 60 percent are differentiated products (as per column 2 of Table 6). Nevertheless, a look at the number of total shipments indicates that products are almost evenly divided between differentiated and homogeneous goods.

# **5. Heterogeneity across Firms and Export Destinations**

This section studies the variation in prices across firms and across destinations with the aim of investigating if the Tanzanian data shows evidence of quality or price competition. The analysis draws from the study undertaken by Manova and Zhang (2012). As these authors highlight, causal interpretation of coefficients is not always possible. In fact, some of the specifications would likely be affected by reverse causality issues. Moreover both dependent and independent variables in some specification might be correlated with firms’ characteristics that cannot be controlled for (a part from including fixed effects).

> 20 The Rauch Classification is a measure of horizontal differentiation, not vertical. An example of horizontal differentiation is the ice-cream, which is produced in different tastes, but one is not necessarily better than the other. 21 Javorcik, B. and Narciso, G. (2008).

11