rafmacalaba/datause-encoder-data huggingface dataset:
decrease in the bilateral price of phone calls is associated with an 8 percent increase in bilateral trade. Moenius (2000) finds that bilaterally-shared and country-specific standards promote trade. Otsuki, Wilson, and Sewadeh (2001a, 2001b) find that 10 percent tighter food standards in the European Union would reduce African exports of certain cereals, nuts, and dried foods by a range of 5 to 11 percent, depending on the category.

WMO (2003) and WMO (2004) developed a new approach to estimate the effects of trade facilitation on trade flows by constructing four measures of trade facilitation, as well as the independent effects of these four on the trade flows among a broad group of countries in the Asia Pacific region and among 75 countries, respectively. In both papers, WMO used cross-country survey data on the business and policy climate to construct numerical measures of trade facilitation for each country for Port Efficiency, Customs Environment, Regulatory Environment and, e-business usage (a proxy for Service Sector Infrastructure importance for trade).

WMO (2003) find that the elasticity of increased Port Efficiency of importing countries is larger than the elasticity of improved Customs Environment or superior Service Sector Infrastructure. If unilaterally applied, more stringent Regulatory Environment will reduce a country’s imports. In their simulations, they find that for the APEC economies as a group, improving Port Efficiency, Customs Environment and Service Sector Infrastructure measures of the below-APEC-average economies half-way up to the APEC average for each trade facilitation measure yields an increase in trade of some 20 percent. Although on average the Port Efficiency indicator is the most important for trade facilitation, since each country has a unique set of indicators and pattern of trade, more detailed analysis of the simulation results shows that for some members of APEC, a trade facilitation measure other than ports may be the best to target for capacity building to increase that economy’s trade.

# **3. Analytic approach**

The following sections draw on WMO (2004) and we reproduce only the key elements of the approach used by the authors. This paper applies an up to date gravity model approach to an updated data set. In contrast to WMO (2004) our approach presented here considers data for main industrial sectors in Mexico. Following WMO (2004), the definition of trade facilitation incorporates relatively concrete “border” elements, such as Port Efficiency and customs 6
19

# lacked the same flexibility in redirecting exports to hard-currency<sup>markets,</sup>

# VmI. RENTS AND RESISTANCE TO REFORM

Under the CMEA system of international trade, exports<sup>were in principle precommitted to</sup> ensure the planned bilateral trade balance, and hence<sup>marketing and other selling efforts as would be</sup> associated with exports to the West were not required<sup>to ensure sustained CMEA sales. Nor was the</sup> "soft-good' output in any event appropriate for western<sup>markets. Enterprises as exporters consequently</sup> had no incentive to seek disengagement from the<sup>CMEA soft-goods economy. Reforms that might</sup> entail a reorientation of international trade towards western<sup>markets could only erode the rents associated</sup> with residual claimancy within the enterprise to CMEA<sup>transaction-specifi</sup><sup>**c**apital.</sup> An enterprise exporting to the CMEA, as part of the<sup>traded goods sector, also potentially</sup> confronted import competition. However, imports<sup>in the planned economy are by their nature</sup> non-competitive with domestic output. Thus in Hungary,<sup>after the abandonment of central planning in</sup> 1968, the enterprises maintained a preference for "planned" CMEA<sup>imports - that is, implicit protection</sup> via CMEA imports that were planned in advance as non-competitive<sup>with their own output. Government</sup> will have exhibited the same preference, insofar as CMEA<sup>trade was a sciurce of employment stability.'</sup> Since Hungary was a "market" rL er than planned economy,<sup>domestic enterprises potentially</sup> confronted competition from western imports. Viability<sup>of the soft-goods enterprises required that</sup> market segmentation with respect to the west be sustained,<sup>via regulation of international trade. There</sup> was no assurance that a tariff could compensate for<sup>soft/hard good quality differences. Exchange</sup> controls and quantitative restrictions were thus required to<sup>preempt import competition.7,</sup> Notwithstanding socialism, the incentives regarding self-interested<sup>stances on protectionism were</sup> 2 See Hillman (1990a). 27See **Gacs** (1989), Oblath (1989).
|P121611|2011|2014|6/23/2014|7 Active|Eastern Africa|
|---|---|---|---|---|---|
|P121611|2011|2015|12/23/2014|8 Active|Eastern Africa|
|P121611|2011|2015|6/18/2015|9 Active|Eastern Africa|
|P121611|2011|2016|12/29/2015|10 Active|Eastern Africa|
|P121611|2011|2017|7/7/2016|11 Active|Eastern Africa|
|P121611|2011|2017|3/7/2017|12 Active|Eastern Africa|
|P121611|2011|2018|3/12/2018|13 Active|Eastern Africa|
|P121611|2011|2019|12/10/2018|14 Active|Eastern Africa|
|P121611|2011|2019|6/19/2019|15 Active|Eastern Africa|
|P121611|2011|2020|1/27/2020|16 Active|Eastern Africa|
|P121611|2011|2021|7/19/2020|17 Active|Eastern Africa|
|P121616|2011|2021|7/22/2020|1 Closed|Nigeria|
|P121620|2010|2010||0 Closed|Bhutan|
|P121643|2013|2013||0 Closed|Vietnam|
|P121643|2013|2014|10/23/2013|1 Closed|Vietnam|
|P121643|2013|2015|7/8/2014|2 Closed|Vietnam|
|P121643|2013|2015|1/28/2015|3 Closed|Vietnam|
|P121643|2013|2016|9/23/2015|4 Closed|Vietnam|
|P121643|2013|2016|3/28/2016|5 Closed|Vietnam|
|P121643|2013|2017|8/1/2016|6 Closed|Vietnam|
|P121643|2013|2017|1/22/2017|7 Closed|Vietnam|
|P121643|2013|2018|7/19/2017|8 Closed|Vietnam|
|P121646|2011|2012|9/1/2011|1 Closed|Central America|
|P121646|2011|2012|5/7/2012|2 Closed|Central America|
|P121646|2011|2013|5/23/2013|3 Closed|Central America|
|P121648|2014|2014|6/8/2014|1 Active|West Bank and Gaza|
|P121648|2014|2015|12/26/2014|2 Active|West Bank and Gaza|
|P121648|2014|2015|6/17/2015|3 Active|West Bank and Gaza|
|P121648|2014|2016|1/6/2016|4 Active|West Bank and Gaza|
|P121648|2014|2016|6/13/2016|5 Active|West Bank and Gaza|
|P121648|2014|2017|12/14/2016|6 Active|West Bank and Gaza|
|P121648|2014|2017|5/23/2017|7 Active|West Bank and Gaza|
|P121648|2014|2018|12/5/2017|8 Active|West Bank and Gaza|
|P121648|2014|2018|6/18/2018|9 Active|West Bank and Gaza|
|P121648|2014|2019|10/2/2018|10 Active|West Bank and Gaza|
|P121648|2014|2019|4/4/2019|11 Active|West Bank and Gaza|
|P121648|2014|2020|10/8/2019|12 Active|West Bank and Gaza|
|P121648|2014|2020|4/1/2020|13 Active|West Bank and Gaza|
|P121651|2012|2012||0 Closed|Turkey|
|P121651|2012|2013|8/14/2012|1 Closed|Turkey|
|P121651|2012|2014|7/4/2013|2 Closed|Turkey|
|P121654|2010|2011|6/3/2011|1 Closed|Ukraine|
|P121654|2010|2013|7/11/2012|2 Closed|Ukraine|
|P121671|2010|2010|6/2/2010|1 Closed|Brazil|
|P121671|2010|2011|6/2/2010|1 Closed|Brazil|
|P121671|2010|2012|6/2/2010|1 Closed|Brazil|
|P121671|2010|2013|6/2/2010|1 Closed|Brazil|
eect of parental matchmaking on love and couple income in urban China. This paper diers from Huang, Jin and Xu (2012) in several ways. First, we oer a formal model and expand the sharable production from joint couple income to many non-marketable household productions such as the number of children and the submissiveness of the wife. Second, we examine the issue from the parents' perspective in old age support and explain why parent matchmaking might aect marriage outcomes dierently in urban and rural areas. When we presented Huang, Jin and Xu (2012) in a conference at the University of Chicago, Gary Becker presented what later became BMS (2015) and encouraged us to go beyond what is in Huang, Jin and Xu (2012) to consider parents' need for old age support.<sup>6</sup> This paper incorporates his suggestions.

Finally, our paper is related to the literature of intergenerational relationship and old age support. Researchers have explored how intergenerational relationships aect old age support (see, for instance, Ikkink, Tilburg and Knipscheer, 1999; Ho, 2007). However, none has explored the role that matchmaking methods play in facilitating old age support.

The rest of the paper is organized as follows. Section 2 describes the theoretical insights, Section 3 summarizes the data, and Section 4 presents the empirical results. A brief conclusion is oered in Section 5.

# 2 Theoretical Framework and Empirical Identication

In this section, we rst present an agency model of parent matchmaking and then interpret it in the context of old age support in rural and urban China. The last subsection discusses empirical implications and how we plan to test them with data.

## 2.1 Agency model of parental matching

Consider the marital decision of a young man, who has nished schooling and started working to earn a living. The search process for a potential wife can either be conducted directly by his parents or by himself. The process that yields a higher net expected utility to him will be implemented. This set up is meant to capture the current practice in China, where marriage in general cannot be forced upon by parents, and males are usually the one who 6One of us (Xu) presented an earlier version of Huang, Jin and Xu (2012) at the Chicago-Remin conference on family and labor economics in 2012 at the University of Chicago, right after Gary Becker presenting an earlier version of Becker, Murphy, Spenkuch (2015). For a new researcher working on marriage topics, having Becker's comment on an early draft was no doubt the best luck he could encounter. (For this, we thank Dali Yang for inviting us to the conference.) Indeed, Becker oered so many constructive comments that he completely changed our perspecitve on the issue. His main suggestions were that we should also consider parental matchmaking from the parents' point of view, that parents might use this method to ensure old age support, that preference might be important (which was a key point in his presentation), and that parental matchmaking may not be inecient given specic institutional and social arrangements.

6
**Table 5:** Fear of Crime and Lower Civic Engagement

||(1)<br>Civic Index|(2)<br>Protest|(3)<br>Community Mtg|(4)<br>Volunteer|(5)<br>Party|
|---|---|---|---|---|---|
|Fear of Crime (Any)|-0.45|-0.14|-0.19|-0.11|-0.26|
||(0.34)|(0.20)|(0.12)|(0.12)|(0.21)|
|Detained at Border|-0.18|-0.14|-0.00|-0.04|-0.08|
||(0.33)|(0.20)|(0.11)|(0.11)|(0.20)|
|Round 3|-0.09|-0.55***|0.30**|0.16+|-0.11|
||(0.24)|(0.14)|(0.10)|(0.09)|(0.14)|
|Female|0.32|0.26|0.06|-0.00|-0.03|
||(0.51)|(0.26)|(0.18)|(0.18)|(0.26)|
|Age|0.02|0.00|0.01|0.01|-0.00|
||(0.02)|(0.01)|(0.01)|(0.01)|(0.01)|
|Indigenous|-0.18|0.04|-0.01|-0.21+|0.29|
||(0.32)|(0.18)|(0.12)|(0.12)|(0.19)|
|Years of Education|0.01|-0.01|0.01|0.01|-0.02|
||(0.03)|(0.02)|(0.01)|(0.01)|(0.02)|
|Tattoo|0.42|0.03|0.17|0.23|0.15|
||(0.77)|(0.33)|(0.30)|(0.31)|(0.37)|
|Children US|0.11|-0.12|0.17|0.05|0.27|
||(0.41)|(0.23)|(0.13)|(0.15)|(0.25)|
|Children GT|-0.13|-0.16|0.03|0.01|0.28|
||(0.32)|(0.21)|(0.12)|(0.11)|(0.22)|
|Assets|-0.10|-0.04|0.06|-0.12|0.31|
||(0.40)|(0.27)|(0.15)|(0.13)|(0.29)|
|ln(Time in US)|0.15+|0.11*|0.01|0.02|0.00|
||(0.09)|(0.05)|(0.03)|(0.03)|(0.05)|
|Employed|0.09|0.20|-0.10|-0.01|-0.14|
||(0.29)|(0.16)|(0.11)|(0.11)|(0.17)|
|Constant|11.09***|3.57***|3.76***|3.76***|2.75**|
||(1.65)|(0.80)|(0.64)|(0.63)|(0.89)|
|Observations|513|513|513|513|510|

Standard errors in parentheses Robust standard errors clustered by respondent + _∗ ∗∗ ∗∗∗ p <_ 0 _._ 10, _p <_ 0 _._ 05, _p <_ 0 _._ 01, _p <_ 0 _._ 001 23
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In sharp contrast to the market for private healthcare, the public sector rewards qualifications and age (experience), but there is no correlation between provider wages and any of our measures of quality including the time spent, checklist completion, correct diagnosis, or correct treatment (Table 7). Since public employees receive non-pecuniary rewards for better performance through more desirable job postings, we also present correlations between the desirability of a posting and measures of quality and again find that the only significant correlate of a better posting is age - suggesting that the public sector does not reward the quality of care provided by doctors with either more pay or with more desirable job postings.<sup>27</sup>

# **6.2 Comparative Cost Effectiveness**

While healthcare in the public sector is free or nominally priced to the user, it is not cost-free to the tax payer. Table A.13 presents estimates of the cost per patient in the public sector, and calculates that the cost per patient interaction is around Rs.240. This is a conservative calculation because it uses only the wage cost in the public sector and thus reflects cost “at point of service” and does not include any cost of infrastructure, facilities, equipment, medicines or administration. By contrast, the fees charged are the only source of revenue for private providers, and hence will cover all operating costs. It also assumes that all patients shown in the official records of the PHC/CHC were true patients. Finally, as is standard in comparative cost effectiveness analysis of this sort, we assume that there is a comparable case mix for primary-health visit across public and private facilities, which is consistent with our data from observing real patients (see section 7.1 below) where we do not find any difference in the symptoms presented across public and private clinics.

# **7 Robustness**

# **7.1 Real Patients**

While the use of SPs to measure quality of healthcare presents several advantages over the next best method of clinical observations. However, SPs are limited in the number and types of cases that can be presented. Further, we may worry that the audit methodology represents

> the public sector and find that both public and private providers have similarly high levels of provision of unnecessary treatments (Table 5).

> 27These results are similar to those found in publicly-provided education in India and Pakistan, where teacher salaries increase with qualifications and seniority, but are not correlated with their effectiveness at raising test scores (Muralidharan, 2013; Das and Bau, 2014). Note that the results are robust to excluding observations where we were not able to identify the medicines provided and classify them as correct or not (see Table A.12).

24
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8 TABLE 2

|iltliorls<br>of$|MAJORGUARANTEED|LOAN PROG|RAMSOF_THE_|U.S.GOVERN<br>_|MENT, 1989||I|
|---|---|---|---|---|---|---|---|
|Program|Description|Coimitments|**X**Subsidy|Subsidy<br>cost|Outstanding<br>commitments|**X**loan<br>termination|Losses|
|Federal Housing<br>Administration|Help families become<br>homeowners|61,790<br>(54%)|1.2%|741|290,729<br>(53%)|1.9%|5,524|
|Veterans'<br>Administration|Mortgage guarantees<br>forveteramnwithno|17,940<br>(16%)|6.6%|1,184|149,957<br>(28%)|1.7%|2,489|
|Export-Import<br>Bank|Guarantees<br>to<br>facilitate<br>U.S.<br>exports|10,200<br>**(**9%)|2.5%|255|5,023<br>**(1%**|||
|Guaranteed<br>Student Loans|Guarantees<br>of<br>education loans to<br>undergraduate<br>ar<br>i<br>graduate students|10,039<br>9%)<br>9%<br>_|33.6%|3,373|42,306<br>8%)|4.4%<br>_|1,861|
|Farmers' Home<br>Administration|Guarantees**Loans**for<br>rura housirg and|3,600<br>**(**3%)|0.8%|29|5,806<br>(1%)|4.7%|275|
|Small Business<br>Administration|Credit assistance to<br>smallbusinesses|3,596<br>**(**3%)|9.1%|327|10,037<br>(2%)|5.6%<br>_|559|
|Commodity Credit<br>Corporationexport<br>Corporationb|Loan guarantees<br>for<br>sales which(<br>mightnot occur<br>otherwise|3,500<br>3%1|13.7%|480<br>**_**|7,846|10.7%|837|
|Foreign<br>Military<br>Sales|Procurement<br>of U.S.<br>mfltftay<br>**ewipiient**<br>and services<br>disasters|2,300<br>(2%)(1)|7.5%|173|7,553|||
|Rural<br>Electrification<br>Administrat!ion|Guarantees<br>of private<br>loans for power<br>gereration|1,319<br>(|17.3%|228|3,583<br>1%)|||
|TOTAL All<br>programs||115,306<br>(100%)|7.6%|8,742.8<br>|544,837<br>I<br>(100%)<br>|2.0%<br>I|10,876|

SOURCE: "Special Analysis **F,"** Speciat Analvses: Budqet of the United States Government, Executive Office of the President, Office of ganagement and Bucget (Washington: U.S. Govermnent Printing Ottice, ¶98), pp. F-79-B7.
# Table of Contents

|I.|Introduction|1|
|---|---|---|
|II.|A Synopsis of Regional Integration Schemes|4|
|II.|The Welfare Economics of Preferential Trading Arrangements|16|
||1.<br>Efficiency Implications<br>2.<br>Rationale for RI Integration|16<br>21|
|IV.|Bargaining, Trading Blocs, and Market Access|25|
|V.|An Evaluation of RI Arrangements|30|
||Growth Effects|32|
|VI.|Conclusions|41|
|Refer|ences|43|
|During the last 12 months (0/1)|||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
||[0.541]|[0.477]|[0.523]|[0.608]|[0.613]|[0.818]|[0.844]|[0.856]|[1.000]|[0.593]|
|Household has a migrant network (0/1)|0.007|0.016|-0.006|-0.006|-0.001|-0.007|-0.004|-0.005|-0.001|-0.006|
||[0.769]|[0.551]|[0.517]|[0.528]|[0.875]|[0.519]|[0.367]|[0.375]|[0.787]|[0.368]|
|Rain - EA level CoV of Dec-Jan rainfall from 1983/84 -|0.900**||0.171|0.164|0.239||0.057|0.056|0.098||
|2012/13|||||||||||
||[0.018]||[0.223]|[0.431]|[0.249]||[0.448]|[0.603]|[0.317]||
|Average 12-month total rainfall (mm)|-0.000|-0.001|-0.000**|-0.000*|-0.000|-0.000*|-0.000**|-0.000*|-0.000|-0.000+|
||[0.745]|[0.209]|[0.020]|[0.061]|[0.201]|[0.100]|[0.013]|[0.055]|[0.190]|[0.130]|
|Annual Mean Temperature (∞C * 10)|0.001|-0.000|0.001|0.001|0.001|0.001|0.000|-0.000|0.000|-0.000|
||[0.659]|[0.919]|[0.515]|[0.554]|[0.494]|[0.632]|[0.975]|[0.988]|[0.667]|[0.968]|
|HH Distance in (KMs) to Nearest Road|-0.001|-0.000|-0.001|-0.001|-0.000|-0.002|-0.001|-0.001|-0.000|-0.001|
||[0.835]|[0.949]|[0.466]|[0.502]|[0.787]|[0.249]|[0.355]|[0.360]|[0.660]|[0.246]|
|HH Distance in (KMs) to Nearest Population Center with<br>+20,000|-0.001|0.000|0.000|0.000|-0.000|0.001+|0.000|0.000|0.000|0.000|
||[0.510]|[0.897]|[0.890]|[0.885]|[0.863]|[0.128]|[0.539]|[0.527]|[0.959]|[0.193]|
|Price of fertilizer in the EA|0.000|0.000|0.000|0.000|0.000|0.000|0.000|0.000|0.000|0.000|
||[0.632]|[0.892]|[0.341]|[0.413]|[0.486]|[0.792]|[0.450]|[0.520]|[0.484]|[0.767]|
|Price of maize grains in the EA|-0.001**|-0.001+|-0.000***|-0.000*|-0.000*|-0.000*|-0.000***|-0.000*|-0.000*|-0.000*|
||[0.022]|[0.112]|[0.003]|[0.055]|[0.054]|[0.059]|[0.008]|[0.083]|[0.063]|[0.084]|
|Time dummy (year 2010=1)|0.010|0.011|0.015|0.015|0.013|0.012|0.010|0.011|0.008|0.010|
||[0.786]|[0.857]|[0.273]|[0.436]|[0.513]|[0.586]|[0.177]|[0.332]|[0.409]|[0.462]|
|Time average included|Included||Included|Included|Included||Included|Included|Included||
|District dummies included|Included||Included|Included|Included||Included|Included|Included||
|Constant||1.578+||||0.629+||||0.388*|
|||[0.137]||||[0.131]||||[0.099]|
|Observations|5,317|5,321|5,317|5,321|5,321|5,321|5,317|5,321|5,321|5,321|
|R-squared||0.130||||0.141||||0.107|
|Number of households||2,764||||2,764||||2,764|

Source: Generated by authors using LSMS data Note: PSLC=Primary School Leaving Certificate. JCE=Junior Certificate Examination. MSCE=Malawi School Certificate of Education Examination. ***, **, *, and + indicate that the corresponding regression APE is statistically significant at the 1%, 5%, 10%, and 15% levels, respectively. The table presents APEs on all explanatory variables. The APEs from the CRE Probit models are estimated using GEE approach. The CRE fractional Probit APEs are from GLM estimation. The unconditional APEs from CRE Tobit are estimated using pooled Tobit regression methods. The linear FE results are presented for comparison purpose. P-values between brackets are based on cluster robust standard errors 55
30

# 1) What the Mincerian regresyipnn show

If individual level (log of) wages or earnings are regressed on years of schooling (or educational attainment) under certain restrictive assumptions it is the case that, following Mincer (1974) the coefficient can be interpreted as a rate of return to schooling. Regressions estimating the Mincerian rate of return have been carried out in a large number of countries and the results are generally quite stable within countries and are reasonably consistent across countries'. Table 10 shows typical results, which show regional average private returns to schooling of various levels. That individuals with higher levels of education earn higher wages is one of the best established facts in economics.

Table 10: Regional averages of the Mincerian rate of retum.

|Region|Avcrage years of schooling in the<br>sample used|Coefficient|
|---|---|---|
|Sub-Saharan Africa|_5.9_|13.4|
|Asia|8.4|9.6|
|Europe, Middle East, North Africa|8.5|8.2|
|Latin America|7.9|12.4|
|OECD|10.9|6.8|

Source: Psacharopoulos, 1993.

Note: The Mincerian rate of return is the simple coefficient on years of schooling in a semni-log regression on or wages._earings This large accumulated body of microeconomic evidence is what makes the macroeconomic evidence above even more interesting. This evidence rules out one obvious response to the finding that, on average, increases in schooling did not increase output per worker. That is, the education provided was of such low quality that it is not surprising that it had no effect on output. This explanation seems to be ruled 44 Montenegro (1995) for instame runs the Mincer regression (which includes a quadratic in experience) on Chilean data for every year fromn 1960 to 1993 and finds tbe coefficient varies from .095 to .167. Funkhouser (1994) runs Mincer regressions for five Latin American countries over several years and finds similar stability. The results are similarly stable in year by year Mincer regressions in the US, where the dramatic role given to the increase in schooling returns in widening income inequality is because it has apparently increased (at the median) from .0635 to .0962 (Bushinsky, 1994).