rafmacalaba/datause-encoder-data huggingface dataset:
**Export Liberalization, Job Creation and the Skill Premium: Evidence from the U.S.-Vietnam Bilateral Trade Agreement**

# **Emiko Fukase**<sup>**1**</sup>

# **The World Bank**

JEL Codes: F16, J23, J24, J31 Keywords — trade liberalization, skill premium, wage, Stolper–Samuelson theorem, Vietnam Sector Board: Poverty Reduction and Economic Management 1 Development Economics Research Group, World Bank. I would like to thank Wim Vijverberg for his advice and support throughout this research; Zadia Feliciano, the late Robert Lipsey and Jonathan Nelson for comments and suggestions; Chad Bown and Will Martin for guidance; and the General Statistics Office of Vietnam for providing the data. I also benefited greatly from comments by Ryan Edwards, Michael Grossman, David Jaeger, Yan Song, Thom Thurston and Merih Uctum. A shorter version of this paper has been published in _World Development_ (2013a). I am grateful to the anonymous referees of _World Development_ and the World Bank for their detailed and very helpful comments. Any remaining errors are mine.

1
6 and the demand price in the home market (PUS). If this rent is bargained over and shared in some way between the Hong Kong license holders and the US buyers, then the import price will lie somewhere between pus and PH. As a consequence, (PHK + L) falls short of pus, that is, the license price is no longer equal to the potential rent. In addition, the Hong Kong price inclusive of the license price, can vary with the quota level, as well as the quota utilization ratio and the concentration in license holdings.

# 1.2 Evidence of Rent Sharing in the MFA

Krishna, Erzan, and Tan (1991) test for rent sharing using data from the United St&tes and Hong Kong. Our approach there was not to point to and model a particular form of market imperfection but instead to test if all the implications of the standard competitive model were borne out in the data. Simply put, if there is perfect competition everywhere, then the license price inclusive Hong Kong price, adjusted for tariffs and transport costs, should be equal to the domestic (US) price of apparel. Other variables such as the quota utilization ratio and the concentration in license holdings should have no effect on this adjusted Hong Kong price.

We tested this hypothesis by regressing the adjusted Hong Kong price on a constant, the United States price, the concentration in license holdings, the quota size, and the quota utilization ratio. We found that we could strongly reject the null hypothesis. Recognizing that our results could be due to compositional differences in US production compared to Hong Kong exports, we developed a way of testing for the existence of such differences. We did not find these compositional differences to be significant on the whole. We also attempted to incorporate some notion of product differentiation by introducing quality differences as fixed effects in the regression. Still, we found that this did not entirely account for the difference in the US and Hong Kong prices.
the problem of a less favorable starting point from which to confront the problems associated with population aging in the next century.

From both the economic and political viewpoints, the most controversial issues confronting the financial sector are the financial troubles of the Ju-Sens and the public funding of any bailout. Because the use of public funds implies an increase in public debt and in the future (or current) tax burden, it is difficult to achieve a national consensus to support ailing financial institutions. On the other hand, the opportunity cost of postponing a decisive set of policy measures to rapidly reduce or eliminate nonperforming loans has been mounting. The time bomb is ticking.

# VI. Model-Based Simulations

This section presents results from a set of macroeconometric, model-based simulations conducted to investigate likely effects on both the Japanese economy and the rest of the world of possible critical events in the ailing Japanese financial sector. Because simulation results are essentially subject to model properties, the aim of these simulations is only to indicate possible qualitative responses of major macroeconomic variables to major financial sector shocks, and to draw implications about shock diffusion under various publicly funded bailout schemes.

## _A. The Model_

This study utilized the fifth-generation EPA World Economic Model created and maintained by the Government of Japan's Economic Research Institute of the Economic Planning Agency for its simulations. This is basically a demand-oriented, Keynesian model with an IS-LM-BP framework, and is made up of the following submodels:20

- 1) three medium-sized country models of the United States, Japan, and Germany (restricted to the former West Germany);

- 2) six small-sized country models of France, the United Kingdom, Italy, Canada, Australia, and Korea;

- 3) six regional models of Asia (excluding Japan and Korea); Western Europe (excluding the countries mentioned above); Latin America; the Middle East; the former Soviet Union and Eastern Europe; and the rest of the world; and

- 4) a trade linkage model.

Our simulations use the medium- and small-sized country models to predict the effects of various policy options. All models employ basically the same specifications in structural equations. The entire system contains 1,234 equations (322 structural equations and 912 identities), the same number of endogenous variables, and 297 exogenous variables.

20 For a detailed exposition of the model, see "EPA WORLD ECONOMIC MODEL - Fifth Version," _EPA World Econometric Model Discussion Papers_ No. 20., Vols. 1 and 2, June 1995.

15
on the 2009 - 2018 period, since further corporate income tax reforms were introduced after 2018. We also drop firms that are not liable for income tax regimes; state-owned firms; and "Individual Enterprises" ( _Personnes Physiques_ ), which should not be liable for the Corporate Income tax. These restrictions reduce our sample to approximately 198,000 firms. Finally, we also drop what we define as "never active" firms – these are firms that are observed at some point throughout the period in the RNE dataset but never register any activity (i.e. positive revenue in tax data, employment in social security, exports or imports in customs).

The sample we obtain, which is the main one we use for the following analyses, is comprised of approximately 96,000 onshore firms and 22,660 offshore firms. In Table 1, – we provide descriptive statistics for this sample in column (1) for the entire panel, and in columns (2) - (6) for selected years. We also document the characteristics of the offshore and onshore sectors in 2013, the year prior to the reform. Approximately 20% of firms in our sample are registered in the offshore regime and 10% of total firms are foreign owned. In terms of sectors, one-third of firms are in manufacturing and one-third in wholesale or retail; the remaining firms are mostly in the services sector (25%).

This is a period of significant expansion in the number of firms in the registry (and our sample), with close to 6 - 7% of firms each year being "entrants", defined as firms we do not observe previously in the panel. The average age of firms is 10 years, but the median is 7 years.

Before providing descriptives for the outcomes of firms in each year, we note that often we observe firms in a given year in the RNE data but information on outcomes can be missing. For that reason, we first document the share of non-missing observations before providing statistics on average values of outcomes of interest.<sup>11</sup> Approximately half of the firms declare employment and wage information in each year - for those, the average number of employees is between 15 - 19 and the average wage bill is approximately 200,000 dinars. The average total revenue is in the range 1.5 - 1.8 million dinars in the

> 11When we consider aggregate outcomes at the sectoral level in the next section, we treat these missing observations as zeros. In our firm level regressions, we restrict our analysis to a balanced sample of firms for which we observe non-missing outcomes in every period.

10
than 2.5 hours, including logistical arrangements (e.g., seating participants and filling exit surveys at the end) and a break.<sup>3</sup>

# _Design Rationale_

The aspirational videos aimed to improve parental attitudes toward education and learning by expanding the choice set they had for their children’s futures. To do so, the documentary videos showed how education may open up a new life and professional trajectories, such as becoming one day a teacher, a doctor or a business person. The animations complemented this message by acknowledging the challenges of combining school activities with work, as well as of the social pressure for girls and families to comply with the common practice of early marriage. The animations gave practical recommendations to deal with both challenges (e.g., how to make time for homework when the child was part of the family business, how to deal with relatives trying to enforce early marriage when wanting to leave daughters in school, among others). Because of the disparities in school enrollment between girls and boys in northern Nigeria, the selected video-clips had a strong focus on girls being equally capable to benefit from schooling and securing occupations useful for the families and communities in the future (e.g., becoming a doctor, teacher, journalist, among others). To make parents reflect on their own circumstances and on possible future scenarios for their children, videos showed _vicarious experiences_ using relatable characters and stories about people living primarily in rural villages in SubSaharan Africa. This is consistent with field experiments that have taken place in this region that have shown that increased program immersion and character-identification is greatly attributed to engaging narratives which are effective at improving attitudes and behaviors of viewers (Banerjee et al. 2019; Berg and Zia 2017).

While talking about the situation of a family member can be perceived as intrusive, we used the approach of Bandura (1997) where we encouraged participants to think about a third person. Towards the end of the community screenings, attendees were asked to reflect upon their own circumstances and use the story narratives as a reference point when the and cons of new behaviors. and to reinforce the assessing pros Finally, program’s self-efficacy messages, facilitators that led the post-screening discussions were asked to emphasize the point that parents’ educational level should not be an obstacle for helping their children to learn.

> 3The authors created a manual to guide facilitators on the key messages of the video-clips, as well as to advise on the time they could spend on each video-clip and discussion of messages. Random checks were done by field coordinators to ensure facilitators followed the agreed protocol.

9
**Figure 3. 9  Banked versus unbanked users of informal savings services**

<!-- Start of picture text --> 100%<br>90%<br>80% 42.7%<br>70% 63.6%<br>60%<br>50%<br>40%<br>30% 57.3%<br>20% 36.4%<br>10%<br>0%<br>Used informal savings during the last Did not use informal savings during the<br>12 months last 12 months<br>Banked Unbanked<br>%<br><!-- End of picture text --> _Source: DANE household study of Bogotá, 2003_

# **3.4 CREDIT SERVICES FOR THE UNBANKED**

22. **Informal credit is used by both the banked and unbanked.** 14% of the survey population uses informal credit services. In line with the finding on informal savings services, demand for informal credit is higher from banked than from unbanked individuals. 58% of informal credit users are banked, while 42% are unbanked. This finding could be partly explained by the fact that the among the unbanked only 9% applied for an informal loan during the past three years, while 20.2% of the banked did, increasing the likelihood of the banked population over the unbanked to obtain informal credit.

**Table 3. 3  Banked versus unbanked users of informal credit services**

||**Banked**|**%**|**Unbanked**|**%**|**Total **|**%**|
|---|---|---|---|---|---|---|
|Uses informal credit|339,061|7.9%|244,300|5.7%|583,361|13.6%|
|Does not use informal|1,338,240|31.2%|2,370,769|55.2%|3,709,009|86.4%|
|credit|||||||
|_Total_|_1,667,301_|_39.1%_|_2,615,069_|_60.9%_|_4,292,370_|_100.0%_|

_Source: DANE household study of Bogotá, 2003_ 54
While politically attractive in the short run, protectionist measures can have large negative repercussions. As a historical precedent, the implementation of retaliatory trade barriers in response to the Great Depression contributed to wiping out around two-thirds of world trade between 1929 and 1933 (Crucini and Kahn 1996; Madsen 2001). Unilateral increases in trade restrictions will most likely be met with retaliatory measures and, eventually, result in sizable increases in worldwide tariffs.

Such an increase in global protectionism is likely to have wide-ranging, economy-wide consequences not only for consumers, but also producers (firms), government, investment and trade flows. First, an increase in tariffs will translate into an effective increase in the price of imported goods for consumers, reducing their purchasing power and limiting the availability of imported goods. Tariffs have been found to disproportionately impact low-income households as these spend more on traded goods as a share of their income (Fajgelbaum and Khandelwal 2016; Furman et al. 2017). Due to their regressive nature, an increase in tariffs is likely to have adverse distributional effects and negatively impact poverty and income inequality. Second, the increase in the price of imported intermediate inputs will force firms to source their inputs from more expensive domestic markets and on the increases in costs to the consumer. This in turn will potentially pass impact firm’s hiring decisions and potentially spill over to changes in wages. Furthermore, given the international fragmentation of production and complex value chains, tariffs may result in cascading trade costs as intermediate goods cross borders multiple times through the stages of production (Diakantoni et al. 2017; Rouzet and Mirodout 2013; World Bank 2017b). Third, the increase in the price of imported capital goods is likely to weigh on investment and disproportionately impact low-income countries (LICs), which rely heavily on imports of machinery and capital goods (World Bank 2017b).

These wide-ranging costs of protectionism can be summarized by a statement made in 1994 by Peter Sutherland, the Director General of the General Agreement on Tariffs and Trade (GATT): "It is high time that governments made clear to consumers just how much they pay - in the shops and as taxpayers - for decisions to protect domestic industries from import competition. Virtually all protection means higher prices. And someone has to pay; either the consumer or, in the case of intermediate goods, another producer. The result is a drop in real income and an inability to buy other products and services."<sup>1</sup> Against this background, the objective of this paper is to showcase the wide-ranging costs of protectionism and implicitly highlight the benefits of (close to) free trade. We quantify

> 1Cited in Manzella Trade Communications (2004).

2
**Table 10: Reduced-Form OLS Regression of Household Consumption Expenditures on Observed Circumstances**

||**COLOMBIA**|**ECUADOR**|**GUATEMALA**|**PANAMA**|**PERU**|
|---|---|---|---|---|---|
|Member of an ethnic minority|-0.043<br>[0.028]|-0.300***<br>[0.023]|-0.411***<br>[0.025]|-1.020***<br>[0.039]|-0.195***<br>[0.017]|
|Father agricultural worker||-0.254***<br>[0.017]|-0.190***<br>[0.023]|-0.202***<br>[0.023]||
|Father primary education|0.196***<br>[0.019]|0.159***<br>[0.018]|0.130***<br>[0.031]|0.171***<br>[0.031]|0.145***<br>[0.019]|
|Father secondary education|0.615***<br>[0.031]|0.470***<br>[0.032]|0.472***<br>[0.046]|0.368***<br>[0.042]|0.364***<br>[0.022]|
|Mother primary education|0.234***<br>[0.019]|0.275***<br>[0.018]|0.374***<br>[0.038]|0.189***<br>[0.030]|0.196***<br>[0.019]|
|Mother secondary education|0.693***<br>[0.033]|0.672***<br>[0.031]|0.725***<br>[0.052]|0.554***<br>[0.043]|0.498***<br>[0.025]|
|Birth region 2|0.202***<br>[0.018]|-0.094***<br>[0.016]|-0.416***<br>[0.033]|-0.028<br>[0.032]|0.051***<br>[0.016]|
|Birth region 3|0.454***<br>[0.023]|0.215***<br>[0.022]|-0.283***<br>[0.028]|-0.257***<br>[0.030]|0.411***<br>[0.023]|
|Constant|14.216***|3.964***|8.520***|6.990***|5.877***|
||[0.020]|[0.018]|[0.029]|[0.039]|[0.017]|
|Observations|22,487|12,643|6,865|5,686|13,649|
|R-squared|0.22|0.31|0.47|0.42|0.31|

Standard errors in brackets. * significant at 10%; ** significant at 5%; *** significant at 1% . Omitted categories are: male, ethnic majority, father and mother with no or unknown education, and birth region 1 (see Table 2 for the country-specific definitions).

43
even stronger – _CIF_ declines from inflows of 7.2 percent of trend GDP to actual outflows of 2.6 percent of trend GDP and _COD_ goes from outflows of 6.5 percent of trend GDP to inflows of 2.6 percent of trend GDP.<sup>23</sup> Despite the similarities in the dynamics of gross capital flows among countries from all income levels, the behavior of net capital flows is rather contrasting. While net capital inflows increase during crises for high-income countries, middle- and low-income countries face a decline in net capital inflows. This evidence is consistent with retrenchment by domestic agents being stronger than that of foreigners in high-income countries but weaker in developing economies.

An event study analysis of gross capital flows around crises reinforces the evidence above. For this exercise, we focus on the dynamics of _CIF_ and _COD_ not only during the crisis years, but also in the run-up to crises and the immediate aftermath by analyzing the two years preceding and following crises. We estimate the following equation: where _Yc_ , _t_ stands for our standardized measures of _CIF_ or _COD_ ; _Crisis_ is the composite crisis indicator; and _Controls_ capture the additional control variables such as country trends.<sup>24</sup> Once more, we perform the analysis by pooling countries according to their income level.

The estimates are presented in Table 5 and Figure 4. They provide robust evidence of retrenchment, that is, capital flows by both foreign and domestic agents decline for countries from all income groups. In particular, both _CIF_ and _COD_ are negative and statistically different

> 23 To the extent that official flows are unlikely to decline during crises, the milder reaction of capital flows in lowincome countries when compared to middle-income ones might be explained by the relative size of these flows. 24 We report results with country trends as controls only, but our results are qualitatively similar if we add year dummies as controls as well.

19
_LcINSP,-,l, Lcc,, Ll, ,Time_ and the constant term. GMM results from equation (3) for water pollution are presented in Table 5, and for air pollution in Table 6.

First, as Tables 5 and 6 indicate, the number of observations used is not the same across equations as a result of missing values in some variables. Second, all equations pass the test of over-identifying restrictions. This indicates that the instruments used are valid. Third, for both water and air pollution, the lagged dependent variable is a relatively good predictor of current pollution emissions. This variable partly reflects the fact that the installation of emissions control equipment is typically a process that requires a long time. To this extent, the lagged pollution variable could also be interpreted as a proxy for changes in the production technology. A similar result was obtained by MV (1990) and LR (1996). Their results were however somewhat stronger than those obtained here. This may be explained by a rapidly changing and growing industrial sector in China. Fourth, water and air related complaints do not appear to have a significant direct impact on pollution. Fifth, state and collectively owned enterprises appear to exacerbate water pollution, at least as far as COD is concemed.

Results of interest concern the impact of inspections and pollution levies. Inspections performed by the Zhenjiang EPB do have a statistically significant negative impact on both water (measured by TSS and COD discharges) and air pollution. The estimations reveal that inspections reduce water pollution by approximately 1.18% and 0.40% for TSS and COD, respectively, and air pollution by approximately 0.34%. These results are lower than those observed in the pulp and paper sector in Canada and the United States where inspections were shown to reduce water pollution by 28% and 20% respectively.

Observe however that the pollution levy does not have a statistically significant impact on pollution. This result differs somewhat considerably from the result obtained by Wang and Wheeler (1999) who used plant-level data across China. In that paper, the authors analyse the impact of the effective levy on pollution emissions in China and found 17
- 8 -

By contrast, many contracts seem to have experienced significant project delays (Figure 6). The sample road works delayed on average 50 percent compared to the original work schedule.

The summary statistics are shown in Table 3. The average number of bidders is six. In the project areas, more than 10 security incidents happened during the 3 months before the contracts, but the significance seems to depend on location. The number of potential contractors may be about 22 firms, out of which only 6 firms actually applied for the competition. On average 26 days are given for firms to prepare their bids. But in some cases, the preparation period looks unreasonably tight, even though rural road works are considered to be simple. In these cases, the entry barrier may be perceived to be significantly high, because there are few firms that could assess work specifications and prepare bids within 6 days.

**Figure 2. Existing road network and districts covered by our sample**

<!-- Start of picture text --> Nepal Roads<br>Districts covered by our sample<br>Nepal DISTRICTS<br>/<br>Source: Benamghar and Iimi (2011).<br><!-- End of picture text -->
-II-

# (1) Sample details

The empirical analysis presented in this paper for the U.S. is based on the balance sheets of a panel of 510 firms for the 1972-1992 period, taken from Standard and Poor's COMPUSTAT data base; the sample excludes firms that were involved in major mergers representing contribution to sales exceeding 50 percent of the acquiring firm's net sales for the year in question. The sample includes industrial firms belonging to manufacturing as well as non-manufacturing sectors that are quoted on the major stock exchanges or over-the-counter. When firms go public initially, their stock is issued over the counter, as they usually cannot meet the listing requirements of major exchanges." In the case of Indian firms, data has been taken from Reserve Bank of India's (RBI) publication titled "Report on Currency and Finance" and Industrial Credit and Investment Corporation of India's (ICICI) publication titled "Financial Performance of Companies" for the 1972-1993 period. As in the case of the U.S., the Indian data too refers to industrial firms that are engaged in manufacturing as well as non-manufacturing activities. However, unlike the U.S., the Indian data includes firms that are not quoted on the stock exchanges.

In the case of the U.S. as well as Indian firms, the data on sources and uses of funds have been derived from their balance sheets. With regard to the issue of the size of the firm, the sample used in this paper for both countries covers the whole range of the size distribution. In the case of the RBI data, there is a distinction between medium and large firms, based on 1s Listing requirements for the New York Stock Exchange currently include: a corporation must have a minimum of one million publicly held shares with a minimum aggregate market value of $16 million as well as net income topping $2.5 million before federal income tax.

17