rafmacalaba/datause-encoder-data huggingface dataset:
# **<mark>Pre-registration</mark>**

<mark>We prospectively registered a protocol of our analysis in the Center for Open Science (OSF) on 10 February 2023 (https://osf.io/jcp2b).</mark>

# **<mark>References</mark>**

<mark>Agostinelli, F., Doepke, M., Sorrenti, G., Zilibotti, F. (2022). When the great equalizer shuts down: Schools, peers, and parents in pandemic times.</mark> _<mark>Journal of Public Economics</mark>_ <mark>206 104574.</mark> <mark>Angrist, N., Djankov, S., Goldberg, P.K., Patrinos, H.A. (2021). Measuring human capital using global learning data.</mark> _<mark>Nature</mark>_ <mark>592(7854): 403-408.</mark> <mark>Angrist, N., Djankov, S., Goldberg, P., Patrinos, H. (2022). Mapping the Global Learning Crisis: Despite record enrollments in school worldwide, learning is limited.</mark> _<mark>Education Next</mark>_ <mark>22(2): 50-56.</mark> Azevedo, J.P., Hasan, A., Goldemberg, D., Geven, K., Iqbal, S.A. (2021). Simulating the potential impacts of COVID-19 school closures on schooling and learning outcomes: A set of global estimates. _The World Bank Research Observer_ 36(1): 1-40.

Belot, M., Webbink, D. (2010). Do Teacher Strikes Harm Educational Attainment of Students? _Labour_ 24(4): 391–406.

Betthäuser, B.A., Bach-Mortensen, A.M., Engzell, P. (2023). A systematic review and metaanalysis of the evidence on learning during the COVID-19 pandemic. _Nature Human Behaviour_ 7(3): 375-385.

Chernozhukov, V., Fernández-Val, I., Melly. B. (2020). Quantile and distribution regression in Stata: algorithms, pointwise and functional inference. Working paper.

Chetty, R., Friedman, J.N., Rockoff, J.E. (2014). Measuring the impacts of teachers II: Teacher value-added and student outcomes in adulthood. _American Economic Review_ 104: 2633–2679.

Currie, J., Thomas, D. (2001). Early test scores, school quality and SES: Longrun effects on wage and employment outcomes. _Research in Labor Economics_ 20: 103–132.

Donnelly, R., Patrinos, H.A. (2021). Learning loss during COVID-19: An early systematic review. _Prospects_ 51: 601-609.

Engzell, P, Frey, A, Verhagen, M. (2021). Learning loss due to school closures during the COVID-19 pandemic. _Proceedings of the National Academy of Sciences_ 118(17).

Goldhaber, D., Kane, T., McEachin, A., Morton, E., Patterson, T., Staiger, D. (2022). The Consequences of Remote and Hybrid Instruction during the Pandemic. NBER Working Paper No. w30010.

15
Policy Research Working Paper 6419

# **Abstract**

This paper explores how the expansion of labor-intensive manufacturing exports resulting from the United States– Vietnam Bilateral Trade Agreement in 2001 translated into wages of skilled and unskilled workers and the skill premium in Vietnam through the channel of labor demand. In order to isolate the impacts of trade shock from the effects of other market-oriented reforms, a strategy of exploiting the regional variation in difference in exposure to trade is employed. Using the data on panel individuals from the _Vietnam Household Living Standards Surveys_ of 2002 and 2004, and addressing the issue of endogeneity, the results confirm the existence of a Stolper-Samuelson type effect. That is, those provinces more exposed to the increase in exports experienced relatively larger wage growth for unskilled workers and a decline of (or a smaller increase in) the relative wages of skilled and unskilled workers. During the period 2000– 2004, the skill premium increased for Vietnam’s economy as a whole in the sample of panel individuals. Thus, the Stolper-Samuelson type effect appears to have mitigated but did not outweigh the impacts of other factors that contributed to the rise in the skill premium.

This paper is a product of the Agriculture and Rural Development 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 author may be contacted at efukase@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
which states that, for all indicators, FAOC-I is met with the same orientation, either decreasing or increasing; 2) _Composite Poverty Ordering Consistency (CPOC)_ stating that the population ordering of an indicator _I_ is preserved with the composite indicator.

FAOC-I is always met with binary indicators. Consistency is always met if one of the two categories of the binary indicator is empty (such as “have” and “not have” some asset). With multinomial indicators and if FAOC-I is not met, the categories can be reorganized so as to meet the property, for example by reducing the multinomial indicator into a binomial one. FAOC-G requires instead that all indicators have the same orientation with respect to the first-axis. This is more difficult to achieve given that some indicators may represent a sub-set of deprivation showing different signs versus the first axis. In this case, we might want to re-elaborate the variable or to eliminate the variable altogether. It is also possible to explore further axes as discussed in Asselin (2009) but this is an option that we won‟t need to follow with our data.

By construction, the weights that result from the MCA procedure average to zero and can have positive and negative values. This is inconvenient for measuring poverty in the second step and it is useful to positively rescale the weight by subtracting the lowest weight from each weight as follows so that the most deprived category of an indicator is always equal to zero and the composite index is always greater or equal to zero. In the paper, rather than rescaling the weights, we will rescale the CWI so that it will become easier to compare this measure with standard monetary measures of welfare such as expenditure per capita.

We will also consider multidimensional poverty over time. This adds the complication of the choice of weights given that we need to have consistent weights over time. One possibility is to merge the two datasets and calculate the weight using both surveys. A second possibility is to calculate the weights in one year and apply the same weights to the other year. We initially tested both approaches and found that the final results were almost identical with a correlation coefficient calculated between the two CWIs of 0.995 and a very consistent ranking of households. We therefore opted for the second approach and used the weights calculated from the second of the two surveys used in this paper. This is the same approach followed by other authors (see for example Asselin, 2009) 7
of the total, in Latin America until 2002 more than half of the outstanding securities were issued in the international capital markets. The declining trend in the ratio for EMs is offset by Asia with a stock of domestic securities that in 2009 is 5 times larger than that of Latin America and 2.5 that of Europe. Indeed the relatively low and stable share of international securities in Asia, between 1% and 3%, is in startling contrast with Latin America where the ratio dropped from over 60% in 2002 to 17% in 2009. In Europe, international securities that were 37% of the total in 1996 reached almost 70% by September 2000, driven by Russia foreign borrowing and then plummeted to 30% in 2009.

**Chart 13**

<!-- Start of picture text --> Ratio International to Domestic<br>0.80<br>0.70 Asia<br>Europe<br>0.60<br>Latin America<br>0.50 EMs<br>0.40<br>0.30<br>0.20<br>0.10<br>‐<br>Source: BIS Quarterly Review Dec. 2009<br>Mar.1996 Sep.1996 Mar.1997 Sep.1997 Mar.1998 Sep.1998 Mar.1999 Sep.1999 Mar.2000 Sep.2000 Mar.2001 Sep.2001 Mar.2002 Sep.2002 Mar.2003 Sep.2003 Mar.2004 Sep.2004 Mar.2005 Sep.2005 Mar.2006 Sep.2006 Mar.2007 Sep.2007 Mar.2008 Sep.2008 Mar.2009<br><!-- End of picture text --> With the domestic debt taking the lion’s share of the government debt portfolios in our sample of EMs we focus next on reviewing the evolution of exposure to rollover and interest rate risk over the last 10 years.

# **Transformation of the Domestic Debt Portfolio**

**Domestic debt portfolios in EMs went through major shifts in composition and maturity in the years that preceded the crisis, reducing the exposure of these countries to shifts in the economic cycle and market sentiment.** This was done while dealing with several constraints that have affected many emerging markets for several years. More stable and sounder macroeconomic policies, together with reforms in the pension and insurance industries, changed the investor base that previously comprised almost exclusively commercial banks. Holdings of domestic institutional investors grew steadily. Pension funds became the second largest group of investors in EMs, with strong presence in countries such as Chile, Malaysia, Uruguay and Colombia. Insurance companies also became increasingly important,

11
They also withhold tax at a rm-specic rate between 0% and 6%.<sup>17</sup> The withheld amount is remitted to the tax authority as advance payment on the sales tax. Card companies are also considered to be highly compliant with their reporting obligation, so that a rm can be relatively certain that its card-machine sales will be reported to the tax authority.

The ling deadline for third-party reports by rms and state institutions is the same as the ling deadline for the income tax, December 15. Credit and debit card reports are led monthly. The tax authority uses all informative declarations, combined with customs declarations on imports and exports, to automatically cross-check all income tax returns. Taxpayers with strong discrepancies between third-party information and the self-assessed tax declaration, and/or meeting other criteria<sup>18</sup> , are selected for partial audits or full audits.

Third-party reports, combined with the list of tax registered rms, are also used to identify nonlers, i.e. rms that have not complied with their ling obligations, for the income tax, the sales tax or third-party reports (reporting transactions with suppliers or clients). The tax authority uses dierent communication interventions, variably relying on emails, phone calls, or personal visits, to follow up with non-lers. However, given human resource constraints, the non-ler campaigns do not systematically cover all non-lers and all ling obligations each year.

# 2.3 Data

The data set used in this paper includes the anonymized income and sales tax returns for 2013-2015 for rms ling in Costa Rica, both corporations and self-employed. This amounts to about 360,000 income tax returns per year and 68,000 sales tax returns per month. The data allows us to measure compliance prior to the experiment (2013), estimate the eect of the experiment on ling for the scal year 2014, and estimate the medium term impact on ling in 2015. The data includes all line items from the tax declarations, and we match it with payment receipts, including advance payments and nal payments, to estimate payment compliance. Finally, we match the rms' declarations with third-party reports submitted by other rms, state institutions, and credit/debit card companies. These data identify sellers and purchasers, transaction types, transaction amounts, and tax withheld where applicable. About 72% of rms who led an income tax return in 2014 were reported by at least one client or supplier, 9% were reported by a credit or debit card company, and 6% by a state

> 17See Brockmeyer and Hernandez (2016) for details on this withholding scheme.

> 18Such as pertaining to specic sectors or reporting a prot rate substantially dierent from the sector specic rate.

10
<!-- Start of picture text --> 80<br>@®@ Poor people<br>70 e ew eo 9% Non-poor people<br>eo @ ad<br>o e®<br>60 fe} ®<br>_<br>iS es. ee e<br>> a . 4 ® r)<br>F=||4 50} @ og “eo co®[e) fe)<br>g 40 oe fe ® )<br><!-- End of picture text -->

<!-- Start of picture text --> =| oF)<br>5 © oP, .<br>> 30} @mpee @ co ae<br>2 re i<br>20 0%,Ss See e@e@<br>eo @<br>ee ro) ®<br>10 ) e@ @ © @ @<br>00 10000 20000 30000 40000 50000 60000<br>GDP per capita (USD)<br><!-- End of picture text -->
rewrite _α_ ̃ _i_ as follows: Now _α_ ̃ _i < αi_ follows from the observation that ( ̄ _Sc − β_ 0 _− βS_ ̄ _p_ ) _>_ 0 in a truncated sample because _S_<sup> ̄</sup><sup>_c_</sup> = _E_ ( _Si_<sup>_c| S_</sup> _i_<sup>_c> Ti_) =</sup><sup>_β_0+</sup><sup>_βS_ ̄</sup><sup>_p_+</sup><sup>_E_(</sup><sup>_εi| εi> Ti−β_0</sup><sup>_−βS_</sup> _i_<sup>_p_)</sup> and _E_ ( _εi | εi > Ti − β_ 0 _− βSi_<sup>_p_)</sup><sup>_>_0.</sup>

# **6.2 Discussion**

The preceding section provides a conceptual basis for the empirical evidence from Bangladesh and India presented in the earlier part of this paper. Here we discuss alternative ways to think about the coresidency bias in the IGC and IGRC estimates which may provide additional intuitions.

We focus on the following relationship between IGRC and IGC widely known in the literature (see, for example, Solon (1999)): A simple way to understand the evidence presented in this paper is that truncation biases the estimate of _β_ downward, but it also results in upward bias in the estimate of ratio of standard deviations in schooling<sup>_σp_</sup> . As a result, the net bias in IGC ( _ρ_ ) is smaller _σc_ than the bias in IGRC ( _β_ ) estimate. Estimate of the ratio of the standard deviations in our data sets confirms that the magnitude is larger in the truncated samples (see Table A.1).

A standard result from the literature is that truncation reduces the variance of a variable (Greene (2012)). Since truncation is based on children’s schooling, it affects the variance of children’s schooling directly : 25
- 11 -

Table 2: RELATIVE PRICES OF THE CPEs' EXPORTS TO THE EEC

||Avera<br>from CP|ge ratio of<br>Es to unit|unit values in imports<br>values in imports froms|
|---|---|---|---|
||Dev<br>cou|eloped<br>ntries|Developing<br>countries|
|Product categories|1982|1984|<br>1982<br>1984|
|Agriculture|1.02|1.01|<br>0.89<br>1.01|
|Animals|1.13|1.12|<br>0.88<br>1.01|
|Vegetable|0.85|0.91|<br>0.74<br>0.94|
|Prepared food|0.92|0.85|<br>0.81<br>1.13|
|Tobacco & beverages|1.39|1.25|<br>1.11<br>1.16|
|Others|1.41|1.41|<br>1.81<br>0.83|
|Raw Materials|1.09|0.99|<br>1.42<br>0.82|
|Ores|2.11|1.43|<br>1.91<br>1.64|
|Mineral fuels|1.08|1.10|<br>0.90<br>0.88|
|Wood|0.85|0.77|<br>0.68<br>0.47|
|Others|0.96|0.87|<br>1.74<br>0.67|
|Manufactures|0.69|0.69|<br>0.81<br>0.78|
|Chemicals|0.89|1.02|<br>0.84<br>0.90|
|Leather goods|0.70|0.76|<br>0.95<br>0.84|
|Rubber goods|0.67|0.64|<br>0.89<br>0.66|
|Wood & paper|0.73|0.71|<br>0.68<br>0.61|
|Textiles|0.66|0.61|<br>0.82<br>0.84|
|Textile articles|0.63|0.61|<br>0.80<br>0.80|
|Ceramics|0.80|0.83|<br>0.76<br>0.75|
|Iron & steel|0.70|0.74|<br>0.77<br>0.88|
|Nonferrous metals|0.63|0.66|<br>0.73<br>0.86|
|Mechanical machinery|0.60|0.61|<br>0.91<br>0.96|
|Electrical machinery|0.55|0.55|<br>0.68<br>0.66|
|Transportation<br>equipment|1.41|1.13|<br>1.08<br>1.15|
|Instruments|0.61|0.55|<br>0.83<br>0.72|
|Others|0.72|0.58|<br>0.84<br>0.71|
|Total|0.75|0.75|<br>0.85<br>0.82|

As the table shows, the CPEs' export prices have been generally lower than those of their competitors and the differences are quite considerable. On average, the relative prices were 25Z lower than EEC export prices in both years. In comparison to LDCs' export prices, the EEC export prices were also higher--by 15Z and 182, respectively, in 1982 and 1984. This implies that the average price level of CPEs exports were even lower than the average level of prices of LDCs in the EEC markets.
- 15 _-_

consumption. Here, we used real M2 (inclusive of foreign currency deposits) as a proxy for the stock of bank loans. We also add the capital account to our equation. Since capital flows are assumed to affect real variables indirectly through their effect on interest rates and the availability of credit, the inclusion of these variables in the regression would be expected to reduce the coefficient on capital flows. The basic equation we estimate is as follows: (1) C = Po + PGDP + P2rir + P3M2 + 4KA + E We estimate this equation for private and public consumption separately, using quarterly data for the period 1987-96. The first column in Table 3 shows the estimated coefficients when the equation excludes real M2.<sup>5</sup> While real income and capital flows are very significant and positive, the real interest rate is found to negatively effect private consumption. The broad results are not significantly altered when real M2 is added to the equation, as seen in the second column. Real M2 enters the equation with a significant positive coefficient. When the availability of credit as proxied by real M2 is controlled for, the significance of the real interest rate declines, but not by a large extent. Interestingly, the results are altered considerably when public consumption is considered.

While one would expect that easier financing due to capital inflows would increase public consumption, the effect of capital flows on public consumption are insignificant. The results are shown in the last two columns of Table 10. The inclusion of real M2 does not alter this result. Although the real interest rate becomes significant along with real M2, capital flows are sltill insignificant. We estimated error correction versions of the equations as well, and finally estimated a parsimonious version of the equations, removing insignificant explanatory variables. The results are broadly the same: private consumption is positively related to capital flows, but public consumption is not. The results are in Table 11.

5 The estimation method used was maximum likelihood allowing for an AR(1) error structure.
**Figure 9. Capital Flows, Average of Group Median Values, (Percentage of GDP)**

<!-- Start of picture text --> 2001-2004 2005-2008<br>24<br>20<br>16<br>12<br>8<br>4<br>0<br>-4<br>-8<br>-12<br>-16<br>EU15 EU Coh. EU11 SEE E. prtn. East Asia LAC EU15 EU Coh. EU11 SEE E. prtn. East Asia LAC<br>FDI Portfolio Other Total Capital Flows CA Balance FX Reserves, change<br><!-- End of picture text --> _Source:_ Gill and Raiser (2012); World Bank staff calculations.

_Note:_ EU coh = EU cohesion countries; E. prtn = EU eastern partnership countries; LAC = Latin America and the Caribbean region; CA = current account; FX = foreign exchange.

**In some cases financial integration and closeness to Western European finance led to excesses, making EU11 countries vulnerable to financial deleveraging of Euro area banks.** Access to finance made it possible to borrow from abroad for investment not only to fuel growth and convergence but also to finance the consumption that has made these economies vulnerable to sudden reversals in capital flows. Financial integration has led to rapid growth in private credit in EU11. The credit growth was supported not only by such supply factors as access to finance but also by demand for housing and consumer durables. Moreover, residential overcrowding in the new EU countries was much worse than in the old EU member states (Figure 10).

12
- Field, E., Jayachandran, S., Pande, R., and Rigol, N. (2016). Friendship at work: Can peer effects catalyze female entrepreneurship? _American Economic Journal: Economic Policy_ , 8(2):125–53.

- Field, E., Pande, R., Rigol, N., Schaner, S., and Moore, C. T. (2021). On her own account: How strengthening women’s financial control impacts labor supply and gender norms. _American Economic Review_ , 111(7):2342–75.

- Gazeaud, J., Mvukiyehe, E., and Sterck, O. (2021a). Cash transfers and migration: Theory and evidence from a randomized controlled trial. _Review of Economics and Statistics_ , forthcoming.

- Gazeaud, J., Mvukiyehe, E., and Sterck, O. (2021b). Enhancing female entrepreneurship through cash grants: Evidence from a randomized controlled trial in Tunisia. _AEA RCT Registry_ .

- Gin ́e, X. and Mansuri, G. (2021). Money or management? A field experiment on constraints to entrepreneurship in rural Pakistan. _Economic Development and Cultural Change_ , 70(1):000–000.

- Gupta, J., Falb, K. L., Lehmann, H., Kpebo, D., Xuan, Z., Hossain, M., Zimmerman, C., Watts, C., and Annan, J. (2013). Gender norms and economic empowerment intervention to reduce intimate partner violence against women in rural Cˆote d’Ivoire: a randomized controlled pilot study. _BMC international health and human rights_ , 13(1):1–12.

- Haushofer, J. and Shapiro, J. (2016). The Short-term Impact of Unconditional Cash Transfers to the Poor: Experimental Evidence from Kenya. _The Quarterly Journal of Economics_ , 131:1973–2042.

- ILO (2018). _Global Wage Report 2018/19: What lies behind gender pay gaps_ . Geneva: ILO.

- ILO (2021). ILOSTAT database. _retrieved from https://data.worldbank.org/ on 1st December 2021_ .

- Imbens, G. W. and Rubin, D. B. (2015). _Causal inference in statistics, social, and biomedical sciences_ . Cambridge University Press.

- Imbert, C. and Papp, J. (2019). Short-term migration, rural public works and urban labor markets: Evidence from India. _Journal of the European Economic Association_ . Forthcoming.

25
19JAMAICA: A number of early reports on Jamaica indicate the lack of a systemic view of tariff reform. It appears that specific industries (footwear, garment, and construction) had been targeted for duty-free import of inputs. In 1983, however, the Bank urged a review of import duties and argued that the exclusion from duty of raw materials, intermediate inputs, and capital goods imports encouraged capital intensity. It suggested that such measures prompted increased taxes on income to replace foregone tariff revenue. As a condition of SAL II, the possibility of imposing duties on imports of raw materials and capital goods while rebating the duties to exporters was to be discussed.

A technical assistance loan in 1985 supported a study of Jamaican comparative advantage and the study recommended a flat rate uniform tariff of 25 percent. The government rejected this proposal and announced a decision to lower tariffs gradually until they corresponded to a 4-rate structure within a 5-30 percent band. This was to be achieved by lowering high rates and raising low rates. In 1987 a trade and finance SECAL included as a condition the review of restricted items by the Bank and the tariff reform commnittee. A maximimum tariff of 60 percent and a minimum of 5 percent were also recommended. Since the nominal tariff was composed of the statutory tariff and so-called stamp duties, tariff reform had to simplify and rationalize this structure. The tariff on raw material and capital goods were to be set at 15 and 20 percent respectively.

TURKEL(: The guiding objectives of a 1985 report were achievement of uniform ERPs across industries and the lowering of average tariffs to 7 percent. In 1987 a Bank study on Turkey commented that average tariffis on intermediate goods were lower than the average tariff on final goods and this indicated that effective protection for final goods production was higher than the nominal tariff rate. However, the report concluded that ERPs give no clear signal for tariff reform since distortion costs depend on nominal tariffs and not ERPs. ERPs may guide reform of the protective structure but this objective is better achieved by production subsidies rather than tariffs.