rafmacalaba/datause-encoder-data huggingface dataset:
# **2. ECONOMY & HOUSEHOLD CHARACTERISTICS**

Vietnam is mostly a rural country; 80% of the population resides in rural areas. Moreover, the incidence of poverty is higher in rural (45.2%) compared to urban areas (10-15%) and 90% of the poor live in rural areas<sup>6</sup> . Agriculture is still very prominent in Vietnam. The population in rural areas is concentrated in the main rice growing deltas: Red River Delta and Mekong Delta. Geographically Vietnam can be divided into two main regions; North and South, where South includes the Mekong Delta and North includes the Red River Delta. These two regions show dramatic differences in production and welfare.

The main staple crop is rice which is cultivated by 80% of the households. Approximately 65% of the cultivated area is under rice. Furthermore, Vietnam is one of the three major rice exporters in the world. Rice constitutes a major part of (around 60%) of the caloric intake for all the households in Vietnam (Minot and Goletti, 2000). Urban households consume less rice per capita than the rural ones. In addition, around 95% (91%) of the urban households are net rice buyers (consume more rice than they produce<sup>7</sup> ). On the other hand, only 49% (53%) of the rural households are net buyers in 1993 (in 1998).

Trade reforms were a major part of the “doi moi” reforms in Vietnam. A series of reforms including (but not limited to) replacement of quantitative barriers with tariffs were implemented in the 90s<sup>8</sup> . Among these reforms the liberalization of rice was central due to the importance of rice in Vietnam. This liberalization had two components: domestic and international. In the international part, Vietnam liberalized the export quota on rice until it was no longer binding in the first part of 1997<sup>9</sup> . Complementing this liberalization was the lifting of internal trade restrictions of rice in 1997. Before this domestic reform, the flow of rice from South (where more rice is produced and there is a surplus) to North was restricted to encourage self sufficiency in each region. The internal

> 6 World Bank (1999).

> 7 A detailed description of net buyer-seller household is provided in the next section.

> 8 See Niimi et al (2003) for a detailed description of the reforms.

> 9 The export quota on rice was abolished in 2001. However, the liberalization in 1997 was very effective as it practically resulted in the quota being redundant.  In fact, Vietnam has switched from being a net importer of rice in 1992 to being the second largest exporter (by volume) of rice in 1998 (Litchfield, McCulloh & Winters (2003).

6
income countries that might have already undertaken the basic macro, institutional, and contractual reforms needed for SME financing to occur. Therefore, in other less developed countries, where minimal reforms have not taken place, macroeconomic and institutional factors might be important binding obstacles and government action in these areas might be needed to enable significant lending to SMEs.<sup>40</sup> Second, banks have learned to cope with a less than perfect macroeconomic, informational, and contractual environment by using products that help to deal with these deficiencies and thus limit risk exposure. For example, banks use short-term loans (mostly for working capital), require collateral and broad guarantees from the SME owners, and focus on products that tend to reduce the risk of SME lending like check discounting, leasing, and factoring. Third, it is also possible that macroeconomic factors are not perceived to be constraining because of the relatively strong growth and benign liquidity and interest rate conditions prevalent in the countries in the sample at the time of the surveys. If the macroeconomic situation in the surveyed countries were to deteriorate significantly, banks might change their perceptions on the prospects for the SME segment. Finally, one would expect that deficiencies in the contractual environment would become more binding as banks try to engage in long-term lending.<sup>41</sup> To be sure, the completion of the questionnaires did help identify important areas for policy action specific to each country. These are discussed in

> 40 Beck, Demirguc-Kunt, and Martinez Peria (2008) survey 80 banks operating in 32 developing countries and find that macroeconomic factors are rated as the top obstacle in this larger sample of countries. However, competition appears as the most important obstacle among the 11 banks from the 7 developed countries included in their study.

> 41 Note, however, that the availability of general purpose long-term bank financing for SMEs might be a problem even in good contractual environments. For example, in the US, only mid-sized firms (among SMEs) appear to be able to obtain private long-term funds, mostly via private placements purchased by life insurance companies (Carey, Prowse, Rea, and Udell 1993 and Berger and Udell 1998).

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Figure 5. Macroeconomic developments during private debt accumulation episodes

# A. Private debt

<!-- Start of picture text --> Percent of GDP<br>60 With crisis<br>Without crisis<br>45<br>30<br>15<br>0<br>t+2 t+8<br>C. Investment and consumption<br>Index t=100<br>180 *** With crisis<br>Without crisis<br>160 **<br>140<br>***<br>120<br>100<br>t+2 t+8 t+2 t+8<br>Investment Consumption<br><!-- End of picture text -->

# B. Output and per capita output

<!-- Start of picture text --> Index t=100<br>With crisis<br>160<br>Without crisis<br>***<br>140<br>**<br>120 **<br>100<br>t+2 t+8 t+2 t+8<br>Output Output per capita<br>D. International reserves and external debt<br>Percent of GDP With crisis Percent of GDP<br>16 *** Without crisis 60<br>12 ** **<br>40<br>8<br>20<br>4<br>0 0<br>t+2 t+8 t+2 t+8 t+2 t+8<br>International Short-term External debt<br>reserves external debt (RHS)<br><!-- End of picture text --> Source: International Monetary Fund; Laeven and Valencia (2018); World Bank.

Note: Figures show the median evolution of macroeconomic variables in debt accumulation episodes with data available for at least 8 years from the beginning of the episode. Year “t” refers to the beginning of rapid private debt accumulation episodes. Episodes associated with crises are those that experienced financial crises (banking, currency, and debt crises, as in Laeven and Valencia (2018)) during or within two years after the end of episodes. “*”, “**”, and “***” denote that medians between episodes associated with crises and those with no crises are statistically different at 10 percent, 5 percent, and 1 percent levels, respectively, based on Wilcoxon rank-sum tests.

A. Private debt in percent of GDP two and eight years after the beginning of the government debt accumulation episode (t).

B.C. Based on real growth rates for output (GDP), output (GDP) per capita, investment and consumption.

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to attend training. We therefore estimate LATE impacts by education level to see whether the effect of actually receiving training varies with education status. We find that receiving training had a larger effect on individuals with a bachelor’s degree for both the savings behavior and retirement savings behavior index (although the heterogeneous treatment effect on savings behavior is only statistically significant at the 10.4 percent level).

# **6.8 Comparison of Treatment and Control Group Outcomes with Administrative Data**

Our partner financial institution provided monthly data on savings and credit card outcomes at the treatment and control group level for the 470 clients found in their data base, from December 2010 through May 2011. This data covers several pre-intervention months since we started inviting clients to the financial literacy course in August 2011. It also overlaps with the follow-up survey, which was conducted between February and July 2012.

Figures 2 to 4 plot the administrative data for the treatment and control group over time. Figure 2 shows that the median savings account balance in the treatment and control group followed a more or less parallel trend before our intervention started in August 2011. In October 2011, the savings balance starts rising in the treatment group, going from about 900 pesos in September 2011 to 1,600 pesos in December 2011, while the savings balance in the control group stays relatively constant. After January 2011, the savings balance in the treatment group starts falling again and goes back to its original level in April 2012. Although the aggregate data does not allow us to conduct a test of statistical significance in the difference of medians, the observed pattern is consistent with the course having a positive effect on savings account balances. However, this effect appears to be temporary.

Figures 3 and 4 displays median credit card balances and average percentage of credit card debt paid off each month, respectively. The treatment and control group values follow a similar pattern throughout the period, indicating no impact of the course on credit card balances or debt paid off each month.

Overall, the patterns in the administrative data are consistent with the follow-up survey results. The course seems to have had no effect on credit card behavior or outcomes, but it led to a small increase in savings. The administrative data suggests that this increase was temporary and dissipated within a few months.

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lower DRD is to be expected, assuming that the death rate declines monotonically with income, though this would have a hard time explaining a _DRD_ so close to unity. However, one cannot rule out the possibility of bias. One reason to suspect underestimation of the _DRD_ using the BR method is greater attenuation bias due to greater noise in the poverty data for Africa.

There are other possible factors. It might also be conjectured that the HIV/AIDS epidemic in Africa may has weakened the correlation between the death rate and poverty. At the early stages of the epidemic, it appears that HIV/AIDS incidence was higher among non-poor groups (at least as indicated by education and living in urban areas). However, there is evidence that this has changed over time, as better educated (and hence less poor) groups were better able to protect themselves from the disease (de Walque, 2004).<sup>12</sup> The very low death rate differential for Africa suggested by the _BR_ method is also hard to reconcile with the aforementioned DHS analyses, which indicate a differential in infant and child mortality rates for SSA between the poorest quintile and overall mean of 1.1, though this is still lower than that for low and middle income countries as a whole (at around 1.4).<sup>13</sup>

# _3.2 Evidence on differential fertility_

Turning next to fertility differentials, one faces similar data problems. The overall Crude Birth Rate (CBR) for low and middle income countries in 2001 is 23 births per year per 1,000 people (World Bank, 2004). Similarly to the death rate, we know less about the conditional mean birth rates, though recent analyses of DHS data have provided some valuable new information.

> 12 There is evidence of lower usage rates for condoms among the poor; the aforementioned analyses of the DHS data indicate a condom usage rate of 18% for the poorest quintile, versus 27% on average (http://devdata.worldbank.org/hnpstats/pvd.asp.).  Against this effect, access to multiple sex partners probably rises with income (at least among males). 13 See at http://www1.worldbank.org/prem/poverty/health/data/index.htm.

13
# **References**

- Adao, R., A. Costinot, and D. Donaldson (2017). Nonparametric counterfactual predictions in neoclassical models of international trade. _American Economic Review 107_ (3), 633–89.

- Albornoz, F., I. Brambilla, and E. Ornelas (2021). Firm export responses to tariff hikes.

- Alfaro, A., J. Castro-Vincenzi, S. Fanelli, and E. Morales (2023). Firm export dynamics in interdependent markets.

- Almunia, M., P. Antràs, D. Lopez Rodriguez, and E. Morales (2018). Venting out: Exports during a domestic slump.

- Amiti, M., S. J. Redding, and D. E. Weinstein (2019). The impact of the 2018 tariffs on prices and welfare. _Journal of Economic Perspectives 33_ (4), 187–210.

- Anderson, J. E. and E. Van Wincoop (2003). Gravity with gravitas: A solution to the border puzzle. _The American Economic Review 93_ (1), 170–192.

- Antweiler, W. and D. Trefler (2002). Increasing returns and all that: A view from trade. _American Economic Review 92_ (1), 93–119.

- Bartelme, D. G., A. Costinot, D. Donaldson, and A. Rodriguez-Clare (2019). The textbook case for industrial policy: Theory meets data. Technical report, National Bureau of Economic Research.

- Bown, C., E. Jung, and E. Zhang (2019). Trump Has Gotten China to Lower Its Tariffs. Just Toward Everyone Else.

- Breinlich, H., E. Leromain, D. Novy, and T. Sampson (2021). Import liberalization as export destruction? evidence from the united states.

- Burstein, A., E. Morales, and J. Vogel (2019). Changes in between-group inequality: computers, occupations, and international trade. _American Economic Journal: Macroeconomics 11_ (2), 348–400.

- Caliendo, L. and F. Parro (2015). Estimates of the trade and welfare effects of nafta. _The Review of Economic Studies 82_ (1), 1–44.

- Caliendo, L. and E. Rossi-Hansberg (2012). The impact of trade on organization and productivity. _The quarterly journal of economics 127_ (3), 1393–1467.

- Cavallo, A., G. Gopinath, B. Neiman, and J. Tang (2021). Tariff pass-through at the border and at the store: Evidence from us trade policy. _American Economic Review: Insights 3_ (1), 19–34.

- Chaney, T. and R. Ossa (2013). Market size, division of labor, and firm productivity. _Journal of International Economics 90_ (1), 177–180.

- Costinot, A., D. Donaldson, and I. Komunjer (2012). What goods do countries trade? a quantitative exploration of ricardo’s ideas. _The Review of Economic Studies 79_ (2), 581–608.

- Costinot, A., D. Donaldson, M. Kyle, and H. Williams (2019). The more we die, the more we sell? a simple test of the home-market effect. _The quarterly journal of economics 134_ (2), 843–894.

- Eaton, J. and S. Kortum (2002). Technology, geography, and trade. _Econometrica 70_ (5), 1741–1779.

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panel presents results from a full model with indicator variables for every possible combination of treatments (no phone and no bin is the omitted category). We generally find statistically significant and positive effects of treatment on recycling behavior when the treatment includes the provision of a bin.

# **<<B>>** Discussion of Participation Intensity Study

The participation intensity results suggest that forgetfulness is not a serious constraint to recycling among households that have already self-selected into the recycling program. Rather, it appears that the inconvenience of storing recyclables for the collectors represents a substantive barrier. Indeed, households reported that they did not want to keep recyclable refuse around the house because it occupies space and attracts insects. This finding is consistent with the case made in Carlson (2001) that reducing the costs incurred by individuals when engaging in proenvironmental behavior is the most effective way to change behavior.

Doing so, however, requires that some resources must be dedicated to reducing those costs. In this context, this is the cost of providing the bin to households. Given that recyclables represent an income stream to the collectors who gather and resell them, it is possible that investing in bin provision represents a profitable prospect, even abstracting from the nonmonetary benefits of additional recycling. To address this issue, we estimate the benefits of investing in bins compared with the provision of one recycling bag per week to each participating family, as is currently done by PRISMA.

Our point estimates suggest that an investment of 14 soles (the cost of a bin without a sticker) leads to an increase of 0.09 soles worth of recyclables turned in by each 27
|**Corporate Governance Benchmark**|**Evaluation of DBSA**|
|---|---|
|The board has ensured that_accounting and_<br>_management information systems_provide the<br>information necessary to determine the costs and<br>results of the_provision of social and public_<br>_services_.<sup>131</sup>|The Balanced Scorecard and Social Accounting<br>Matrix frameworks seek the measure the results<br>of DBSA’s developmental activities. The Bank’s<br>contributions to the Developmental Fund are<br>clearly identified and reported. The Bank might<br>be able to make more explicit its accounting for<br>and reporting of the costs of activities undertaken<br>by the Bank itself on less than a fully commercial<br>basis.<sup>132</sup>|
|The board uses explicit_procedures to ensure the_<br>_integrity of financial and non-financial_<br>_reporting_.<sup>133</sup>|See above comments regarding the Audit and<br>Finance Committee.|
|The board, by means of the annual Directors’<br>Report and/or published financial statements, is<br>explicit about how it_balances tradeoffs between_<br>_financial objectives, social service objectives and_<br>_developmental objectives_.|The Directors’ Report in the Annual Report<br>reports extensively on performance against<br>objectives, including by disclosing performance<br>against the targets set out in the Balanced<br>Scorecard. The Directors’ Report addresses<br>economic/financial, environments and social<br>outcomes. See section 4.|
|The board undertakes an_annual self-evaluation_to<br>appraise its performance. The evaluation<br>scrutinizes the performance of the overall board,<br>the chairperson, and individual members. It<br>assesses, among other matters, the adequacy of the<br>mix of the skills and experience of the board, and<br>the processes for nomination and election of board<br>members and for management of conflicts of<br>interest. The results of the evaluation are<br>communicated to the ownership entity.|The Protocol sets out requirements for an annual<br>assessment of the performance of the Board,<br>requiring a review of its size, mix of skills,<br>expertise and experience, and covering the Board<br>collectively, the Chairperson, the CEO and each<br>individual Board member. The assessment is to<br>measure performance in achieving the objectives<br>set out in the required Shareholder Compact. The<br>Board Charter specifies that the Chairperson must<br>annually report to the shareholder on the<br>performance of each Board member and the<br>Board collectively, and specifically review areas<br>in which the Board or its functioning could be<br>improved. As an example, in the 2004/05<br>financial year, the review determined that<br>improvement was required in terms of continuous<br>provision of information and training on business<br>and accounting developments.|

> 131 This might, for example, include maintaining separate accounts for such activities. 132

> **_DBSA_** : For example, the interest income forgone by charging below market interest rates on loans. 133

> **_Good Practice_** : Board members sign publicly disclosed financial reports.

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|Reported de jure FHH|10.39|10.55|6.26<br>|6.26|4.54|3.98|12.76|13.34<br>|30.16|31.50|8.69|9.28|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Reported married FHH|12.7|10.49|13.20<sup>*</sup>|6.17|0.00|4.20|9.25|13.42<sup>*</sup>|36.90|31.19|8.97|9.18|
|Potential FHH|6.24|11.58<sup>*</sup><br>|5.05|6.36<br>|0.81|4.77<sup>*</sup><br>|11.70|13.58<sup>*</sup>|23.57|32.92<sup>*</sup><br>|7.74|9.57<sup>*</sup><br>|
|Core FHH|7.59|10.65<sup>*</sup><br>|1.33|6.39<sup>*</sup>|0.00|4.33<sup>*</sup><br>|11.32|13.31|23.75|31.66<sup>*</sup><br>|7.38|9.29<sup>*</sup>|
|Asset FHH|6.14<br>|11.29<sup>*</sup>|4.76<br>|6.36|0.68|4.72<sup>*</sup><br>|12.19<br>|13.42|25.22<br>|32.03<sup>*</sup>|8.97<br>|9.21|
|Share of female adults>0.5|12.16<sup>*</sup>|9.89|8.69<sup>*</sup>|4.83|2.74|4.86<sup>*</sup>|15.30<sup>*</sup>|11.80|33.93<sup>*</sup>|29.72|11.40<sup>*</sup>|7.91|
|Share of employed<br>females>employed males|8.79|10.7<sup>*</sup>|3.09|6.57<sup>*</sup>|0.47|4.64<sup>*</sup>|10.29|13.61<sup>*</sup>|31.32|31.29|10.27<sup>*</sup>|8.99|
|Most educated member is female<br>adult & no employed males|8.74|10.90<sup>*</sup>|9.36<sup>*</sup>|5.84|3.02|4.41|10.04|14.05<sup>*</sup>|35.36<sup>*</sup>|30.23|11.40|8.51|

Note: The data are pooled across all available years for each country. Headcount poverty rates are estimated using per capita household expenditures. Stars indicate statistically significant difference in headcount poverty between FHHs and non-FHHs in each category at the 5% or lower level. Population sampling weights are applied.

53
# **6. Annex**

**Table 9: Public expenditure (in real terms) on MDG-related services: baseline**

||200|4|201|5|Average gr|owth (%)|
|---|---|---|---|---|---|---|
||Per capita<br>(000 LCU)|<br>% of GDP|Per capita<br>(000 LCU)|<br>% of GDP|Per capita|% of GDP|
|Total spending (ex. transfers and interest)|896|24.5|1,246|21.7|3.05|-1.11|
|Social spending|556.1|15.3|717.2|12.6|2.34|-1.78|
|General government. spending|339.5|9.2|529.1|9.1|4.12|-0.08|
|Total social spending by type|||||||
|Current spending|238.5|6.73|296.8|5.34|2.01|-2.08|
|Wages|220.3|5.97|274.0|4.72|2.01|-2.11|
|Non-wage|18.2|0.8|22.8|0.6|2.04|-1.83|
|Investment spending|317.6|8.61|420.4|7.25|2.58|-1.56|
|Share of current spending|42.9||41.4||||
|Share of investment spending|57.1||58.6||||
|Total social spending by activity|||||||
|Primary education|105.6|2.86|122.8|2.12|1.38|-2.71|
|Secondary education|121.3|3.29|131.7|2.43|0.75|-2.71|
|Tertiary education|71.8|1.95|77.9|1.44|0.75|-2.71|
|Health|107.2|2.91|136.5|2.88|2.23|-0.08|
|Water and sanitation|26.5|0.72|31.2|0.62|1.50|-1.38|
|Publicinfrastructure<br>_Note_: LCU stands for local currency units|133.5|3.62|157.2|3.11|1.50|-1.38|

**Table 10: Composition of public spending on MDG-related services: baseline**

|||2004|2010|2015|Annual growth<br>(2004-2015)|
|---|---|---|---|---|---|
|_Government current MDG-_|_related expenditur_|_es_||||
|Primary education|(bn lcu)|1,825|2,306|2,801|4.0|
|Secondary education|(bn lcu)|1,322|1,671|2,030|4.0|
|Tertiary education|(bn lcu)|930|1,175|1,428|4.0|
|Health|(bn lcu)|1,045|1,548|2,149|6.8|
|Water and sanitation|(bn lcu)|45|61|80|5.4|
|Public infrastructure|(bn lcu)|210|287|374|5.4|
|_Government MDG-related i_|_nvestment_|||||
|Primary education|(bn lcu)|463|585|711|4.0|
|Secondary education|(bn lcu)|1,306|1,650|2,004|4.0|
|Tertiary education|(bn lcu)|625|789|959|4.0|
|Health|(bn lcu)|1,277|1,893|2,628|6.8|
|Water and sanitation|(bn lcu)|529|724|942|5.4|
|Publicinfrastructure|(bn lcu)|2,682|3,675|4,778|5.4|

_Note:_ Annual growth rate for investment in primary education is calculated for the 2004-2010 period.

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