rafmacalaba/datause-encoder-data huggingface dataset:
maquila-- might reduce migration.<sup>2</sup> In a times series context, Hanson and Spillimbergo (1999) find that border apprehensions are responsive to US-Mexico wage differentials, a finding confirmed by McKenzie and Rapoport (2003) using a retrospective survey. Davila and Saenz (1990) find a negative relationship between lagged maquila employment on the border and monthly border apprehensions as a proxy for migration pressures. Unfortunately, more direct trade data on FDI and trade are available neither at the level of periodicity or span to offer enough degrees of freedom to permit inference with any confidence. Further, the massive peso crisis beginning roughly concomitant with the signing of NAFTA led to a sharp spike in unemployment and a 25% fall in wages. These likely induced flows to the US that complicate inference on the more modest effects that NAFTA might have had in the opposite direction.

For these reasons, this paper focuses on evaluating the mechanisms through which NAFTA related variables might work using data on migration flows _within_ Mexico where the 2000 census data permit careful analysis and the 32 by 32 permutations offer substantial degrees of freedom. Figure 1 shows the rates of net migration (net flows as a fraction of the population in the initial period) by state and figure 2 FDI by state. A casual look suggests that, in fact, there is a relationship between the magnitude of FDI and migration to a locale. In investigating this possibility for FDI and other trade variables more rigorously, we make three contributions to the literature on migration more generally, and then specifically on the impact of trade and FDI flows on migration.

First, we offer the first estimates of determinants of migration flows within Mexico and make some advances in the less developed country (LDC) migration literature. In line with recent innovations in the industrialized country literature, we generate proxies for both the level of amenities and costs of living and find their influence to be statistically significant. Further, contrary to much of the literature either in the industrialized or developing world noted above, our specification allows

> 2 Using data gathered in 25 Mexican communities, Massey and Espinosa (1997) create histories of migrants to the US and find initial migration to the US to be negatively related to the wage rate and the proportion of women in manufacturing.  Jones (2000) examines 17 emigrant municipalities and argues in favor of an association between proximity to maquiladoras and employment growth and, in turn, declining US migration.

2
orities (allocative e¢ ciency), and (iii) public goods delivery that is cost e¤ective (technical e¢ ciency). We classify MTEFs into three phases: Medium-Term Fiscal Framework (MTFF, which establishes the aggregate resource envelope), Medium-Term Budget Framework (MTBF, which focuses on the allocation of spending across sectors, programs and agencies) and Medium-Term Performance Framework (MTPF, which sets sectoral performance targets). These three MTEF phases are “nested”: an MTPF contains an MTBF, which in turn contains an MTFF.<sup>5</sup> The new data reveal patterns in the timing of MTEF adoption across regions and levels of development. OECD countries were the ...rst to adopt MTEFs, and by the early 1990s most countries in this group had an MTPF in place. The bulk of MTEF reforms in SubSaharan African countries took place in the 1990s, Latin American countries adopted MTEFs in the late 1990s, and Eastern Europe and the former soviet republics joined the trend in the 2000s. We exploit di¤erential patterns of MTEF adoption across regions to construct external instruments that complement the standard GMM-style internal instruments.

The empirical results show that MTEFs strongly improve ...scal discipline and that the e¤ect is larger the more advanced the MTEF phase. The e¤ect varies between 1 and 3 percentage points of central government balance as a percentage of GDP. We also ...nd that MTBFs and MTPFs improve allocative e¢ ciency, measured by the volatility in per capita health spending in purchasing power parity dollars (PPP$), and that MTPFs contribute to technical e¢ ciency, measured as technical e¢ ciency scores from a stochastic frontier model of public health delivery. These results are robust to excluding highly autocratic and highly developed countries.

Our results are more favorable about MTEF e¤ectiveness than the conclusions of prior work. Bevan and Palomba (2000), La Houerou and Talierco (2002), Holmes and Evans (2003), and Oyugi (2008), based on case studies of about a dozen African countries, conclude that the budget process has generally not improved after the adoption of an MTEF, while McNab, Martinez-Vasquez, and Boex (2000) and Oxford Policy Management (2000) raise questions of adequate implementation. However, Gleich (2003) and Ylaoutinen (2004) ...nd that MTEFs in Central and Eastern Europe alleviated the de...cits and debts that emerged in the second half of the 1990s. Wescott (2008) and Filc and Scartascini (2010), using data from Central and Latin America, found mixed results and emphasized the importance of piloting MTEFs in areas where they are likely to deliver the largest payo¤.<sup>6</sup>

> 5This taxonomy follows World Bank (2012) and borrows from Castro and Dorotinsky (2008) with the nesting concept as an added innovation.

> 6Drawing on extensive operational experience with MTEF implementation in developing countries,

4
Gregorio Impavido Market concentration has been decreasing but remains fairly high. The participation of the largest five providers in total gross premium written (CR5) has decreased from 85 percent to 72 percent between 1997 and 2001 and remained stable since that year.

The pension annuity market in Mexico is very small. This is due to the fact that the pension reform that created it was conducted only in 1997 and because the Mexican insurance market in general has low penetration and density (1.7 percent of GDP and MXN 1,389 per capita, respectively in 2005). Table 6 reports the evolution of the major business lines of the Mexican insurance market between 1997 and 2005. The gross premium related to the annuity market increased from 3.2 percent to 13.2 percent of total insurance gross premium income between 1997 and 2001 while it decreased again to 3.3 percent in December 2005.

**Table 6: Insurance Sector Business Lines Growth (1997–2005)**

|**(Percent)**|**1997**|**1998**|**1999**|**2000**|**2001**|**2002**|**2003**|**2004**|**2005**|
|---|---|---|---|---|---|---|---|---|---|
|Motor|25.8|25.5|23.8|25|24.7|24.2|26.9|24.4|25.1|
|Other P&C|25.9|20.4|18|16.8|17.4|18.5|21.4|20.3|18.9|
|Life|35.2|31.7|36.1|34.2|33.7|39.1|36|38.9|37.9|
|Accidents &<br>Health|9.8|8.9|9.4|10.6|10.9|10.9|12.9|12.7|14.8|
|**Pensions**|**3.2**|**13.5**|**12.7**|**13.2**|**13.2**|**7.3**|**2.7**|**3.7**|**3.3**|
|Total GPI||||||||||
|(MXN mln)|78,639|94,811|101,001|110,320|125,699|140,928|128,063|142,640|138,377|
|1/||||||||||
|GPI/GDP<br>(percent)|1.3|1.5|1.6|1.6|1.8|2.0|1.8|1.9|1.7|
|GPI/Pop.<br>(MXN)|839|999|1,051|1,133|1,273|1,408|1,263|1,389|1,331|

**Notes** : 1/ Real 2005 pesos. . **Source** : CNSF, IFS, WDI.

Table 7 summarizes the growth of the pension annuity market in terms of key variables between 1997 and 2005. The number of annuitants for the benefits of IV and RT increased every year between 1997 and 2002. Afterwards, figures decreased sharply. The number of eligible annuitants increased from 6,068 in 1997 to 30,778 in 2001. The number of individuals who had bought a pension annuity from private sector providers increased from 4,410 in 1997 to 30,824 in 2001. In the ensuing years the number of eligible individuals and actual annuitants decreased to around 7,900 in 2005.

The same pattern can be observed in the value of pension annuity premiums with the exception of 2004 when a spike in premiums written can be observed.<sup>5</sup> Between 1997 and 2001, gross written premium increased from MXN 2,522 million (annualized) to MXN 16,641 million. In the ensuing months it decreased to reach MXN 4,504 million in

> 5 That was due to an amendment to the LSS-97 that increased the pension amount to those pensioners satisfying the legal requirements established by that amendment.  This implied a transfer of almost $1,700 million MXN of single premium to the annuities companies.

- 6 -
Based on KLEMS labor productivity, we compare more disaggregate sub-sectors in EU-8 countries. Besides real estate activities, the other sub-sector that ranks among the top five in terms of productivity in 5 or 6 EU-8 countries is activities auxiliary to financial intermediation (NACE 67) and renting of machinery and equipment (NACE 71).<sup>17</sup> Hotels and restaurants and wholesale trade rank consistently among the least productive sub-sectors in EU-8 countries. The consistency in the ranking of services subsectors across ECA countries according to their labor productivity suggests that ‘technological’ characteristics such as capital intensity may play a role similar to what they play in explaining diverse labor productivity across manufacturing sub-sectors.

Comparing labor productivity of a given sub-sector across countries is not subject to the ‘apples and oranges’ criticism as one is comparing ‘apples’ produced under different economic environments. This may in fact indicate which environments encourage better performance by a sub-sector. However, this comparison is subject to the problem of cross-country heterogeneity in price and quality of the ‘apples’. The use of expenditure-based PPPs (WIIW labor productivity) deals away only with general differences in price levels across countries, while the use of sub-sector specific production-based PPPs (KLEMS labor productivity) deals away with sub-sector specific differences in price levels across countries. To the extent that different prices reflect well differences in quality, the use of PPPs also mitigates the problem of different services’ quality across countries.

Figure 8 shows WIIW labor productivity for each services sub-sector in ECA countries averaged in 1997-2000 and in 2001-2004. The evidence suggests a different ‘comparative advantage’ for different countries as no single country exhibits the highest WIIW labor productivity in all sub-sectors. Slovenia and the Czech Republic exhibit the highest, while Romania exhibits the lowest productivity in electricity, gas, and water. In wholesale, retail, and repair of motor vehicles, Poland is the most efficient while Ukraine is the least efficient. Poland’s efficiency in wholesale, retail, and repair of motor vehicles is likely related to the importance of FDI in that sub-sector. Unfortunately we lack the data necessary to confirm this hypothesis. Romania displays the highest while the Slovak

> 17 NACE 67 comprises administration of stock or commodity exchanges, security broking and fund management, and mortgage brokers.

18
# **Table 1: Views of Austrian Health Actors**

||**What do you think**<br>**about cross-border**<br>**purchasing?**|**Do you expect**<br>**financial cost savings?**|**What are the main**<br>**problems?**|
|---|---|---|---|
|Federal Ministry for<br>Social Affairs|Ambivalent|No|Domestic tensions<br>(income pressure on<br>Austrian service<br>providers); tariffs|
|Viennese HIF|Minor concerns<br>(concurrence for<br>Viennese health<br>facilities)|No (in the contrary<br>expects additional costs)|Tariffs; quality control;<br>influence on domestic<br>contracts and tariffs;<br>follow-up treatments;<br>claimsforcompensation|
|Salzburg HIF|Only for specific<br>treatments|No (in the contrary<br>expects additionalcosts)|Quality of the benefits;<br>cost effectiveness|
|Medical Association|Only if same quality is<br>being delivered|-|Conformity with<br>Austrianstandards|
|Private health insurance<br>provider|In principle cheaper but<br>structures are missing|Not under the current<br>conditions|Interplay between<br>public and private<br>health insurance; lack of<br>EUharmonization|
|Hospital operator|Cross-border contracts<br>would be welcome;<br>only in specific areas;<br>will be a temporary<br>phenomenon|No|Tariffs; legal<br>uncertainties; lack of<br>EU harmonization|

# **3.2 Hungarian Health Actors**

The following paragraphs will shortly summarize the views of Hungarian health care actors along two issues: What size does the phenomenon of cross-border purchasing have, and is it growing? Are foreign patients perceived to be a good business opportunity?

# **3.2.1 National Health Insurance Fund (NHIF)**

According to the Hungarian NHIF, 99 percent of Austrian patients who receive dental treatment in Hungary do it via the out-of-network way, as private patients. There are endeavors—though not yet very concrete—to increase cross-border cooperation in health care with Slovakia, i.e. cooperation between Northern Hungary and Southern Slovakia. There are few efforts to encourage trade in health care (e.g. spa treatment), but those benefits do not fall under the EC regulations or are not financed by the NHIF. For spa treatment, more German than Austrian patients travel to Hungary.

# **3.2.2 Association of Human Private Health Care Providers**

According to the Hungarian Association of Human Private Health Care Providers, the main obstacles to cross-border purchasing are on the one hand the immobility of patients and on the other hand the lack of public financing. The association assumes that the public sector would be in principle interested in cross-border care, because the health sector in Hungary is structurally underfunded. Therefore, patients from abroad could generate additional resources. However, the Hungarian NHIF cannot calculate a higher 13
# **Table 23h.  Piecemeal Sensitivity Analysis –Carbon Monoxide Emissions by Region from WTO Accession (percentage change from base year)**

|||**Overall**||**Far**||||||**St.**|||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|**Parameter being **|**changed**|**average**|**Central**|**East**|**North**|**Siberia**|**South**|**Urals**|**Moscow**|**Peters.**|**Tumen**|**Northwest**|
|**Central Results f**|**or reference**|4.5|17.0|3.5|4.8|3.4|5.8|4.4|9.9|13.6|2.7|9.8|
|**esubc = 0.5**||4.5|16.5|3.5|4.9|3.4|5.5|4.4|10.4|14.6|2.7|9.7|
|**esubc = 1.5**||4.5|17.2|3.6|4.8|3.4|5.9|4.5|9.7|13.7|2.7|9.8|
|**esub = 2**||3.6|13.4|3.5|4.3|3.1|4.5|3.3|6.0|10.8|2.3|9.4|
|**esub = 4**||4.8|18.3|3.5|5.2|3.6|6.2|4.9|12.1|14.7|2.8|9.7|
|**esubs = 0.5**||3.8|15.5|2.5|3.9|2.9|4.9|3.9|9.8|10.6|2.3|8.0|
|**esubs = 2.0**||5.4|19.7|5.5|6.4|4.3|7.2|5.3|10.2|16.1|3.3|12.9|
|**esubva = 0.5**||4.3|16.7|3.2|3.4|3.2|5.9|4.4|8.6|12.7|2.7|9.5|
|**esubva = 1.5**||4.5|17.2|3.7|4.9|3.5|5.7|4.4|10.5|14.1|2.7|9.9|
|**etad = 10**||4.6|18.0|3.3|4.9|3.6|5.9|4.6|10.9|15.4|2.7|9.1|
|**etad = 5**||4.3|16.1|4.0|4.8|3.3|5.6|4.3|8.8|11.7|2.8|11.0|
|**etadx = 3**||4.3|14.8|3.3|3.6|3.4|5.5|4.3|9.8|12.2|2.8|8.1|
|**etadx = 7**||4.7|19.1|3.9|4.9|3.4|6.1|4.6|10.3|15.5|2.6|11.3|
|**etaf = 12.5**||4.1|15.2|3.8|4.7|3.5|5.1|3.9|9.4|12.1|2.3|8.6|
|**etaf = 17.5**||4.8|18.7|3.3|5.0|3.3|6.3|4.9|10.4|15.1|3.1|10.8|
|**sigmadm = 4**||4.8|18.0|3.6|5.0|3.7|6.1|4.8|11.6|14.9|2.8|10.1|
|**sigmadm = 2**||3.8|14.5|3.5|4.5|3.1|4.8|3.6|7.1|11.2|2.3|9.1|
|**Source: Authors' cal**|**culations.**||||||||||||
|**Notes:**|||||||||||||
|a. Thepiecemeal sens|itivityanalysis em|ploys centr|al values for al|lparameter|s(see below|)other than t|he testedpa|rameter.|||||
||**Parameter**|**Central**|**Definitions of**|**theparame**|**ter(see figur**|**es, especiall**|**y figure 5)**||||||
|||**value**|**for moreprec**|**ise elastici**|**ty structure).**||||||||
||esubc|1.25|Elasticityof su|bstitution in|consumer d|emand|||||||
||esubs|1.25|Elasticityof su|bstitution b|etween value-|added and bu|siness servi|ces|||||
||sigmadm|3|"Armington" el|asticityof su|bstitution be|tween imports|and domest|icgoods|||||
||etaf|15|Elasticityof m|ultinational|service firm s|upplywith res|pect toprice o|f output|||||
||etad|7.5|Elasticityof R|ussian servi|ce firm suppl|ywith respect|toprice of ou|tput|||||
||esub|3|Elasticityof su|bstitution b|etween firm v|arieties in imp|erfectlycomp|etitive sectors|||||
||esubva|1|Elasticityof su|bstitution b|etweenprima|ryfactors ofpr|oduction in v|alue added|||||
||etadx|5|Elasticityof tra|nsformation|(domestic o|utput versus e|xports)||||||

74
# **Abbreviations**

|ADB|Asian Development Bank|
|---|---|
|<br>AEC|<br>ASEAN Economic Community|
|AHTN|ASEAN Harmonized Tariff Nomenclature|
|APEC|Asia-Pacific Economic Cooperation|
|ASEAN|Association of Southeast Asian Nations|
|ASYCUDA|Automated System for Customs Data|
|CB|Capacity Building|
|CEFACT|Center for Trade Facilitation and Electronic Business|
|CSI|Container Security Initiative|
|C-TPAT|Customs-Trade Partnership against Terrorism|
|DTIS|Diagnostic Trade Integration Study|
|ICC|International Chamber of Commerce|
|EDI|Electronic Date Interchange|
|EDIFACT|Electronic Data Interchange for administration, commerce and transport|
|EU|European Union|
|FIATA|International Federation of Freight Forwarders|
|FTA|Free Trade Agreement|
|GATT|General Agreement on Tariffs and Trade|
|GDP|Gross Domestic Product|
|GFP|Global Facilitation Partnership|
|GMS|Greater Mekong Sub-region|
|ICT|Information Communication Technology|
|IMF|International Monetary Fund|
|IMO|International Maritime Organization|
|ISPS|International Ship and Port Facility Security Code|
|IT|<br>Information Technology|
|ITC|International Trade Commission|
|MFN|Most Favored Nation|
|MRA|Mutual Recognition Agreement|
|OECD|Organization for Economic Development and Cooperation|
|OSC|Operation Safe Commerce|
|PSI|Pre Shipment Inspection|
|RTA|Regional Trade Agreement|
|SCM|Supply Chain Management|
|SCO|Shanghai Cooperation Organization|
|SITPRO|<br>Simplifying International Trade|
|SME|<br>Small and Medium Enterprise|
|SPS|Sanitary and phyto-sanitary standards|
|SSI|<br>Single Stop Inspection|
|STAR|Secure Trade in the APEC region|
|SWEPRO|Swedish Trade Procedures Council|
|SWI|Single Window Inspection|
|TA|Technical Assistance|

2
tax is designed to replace the current oil excise tax on an elective basis. For the companies electing not to switch to that system, a new differentiated excise tax would be adopted. In addition, the drafts provide for a widening of the royalty band (Lapyunova and Reznik 2000). The TAPFFE would work in the following way: all the sales revenues accumulated since the beginning of a project would be divided by the accumulated eligible costs, to determine a socalled "R-factor" for each site. The size of the R-factor would then determine the tax rate. The tax base would be defined as accumulated revenues minus accumulated costs with some corrections. The TAPFFE takes a long-term approach to taxation as it considers all revenues and costs accrued since the first year of the project. Table 6 shows one of the latest proposals of tax rates.

Table 6. Proposed Tax on Additional Profits from Fossil Fuel Extraction

|R-factor<br>Tax rate|
|---|
|<1.0<br>0%|
|1.0-1.3<br>20%|
|1.3-2.0<br>40%|
|>2.0<br>60%|

Source: Ministry of Finance.

2.12 Some of the problems with the TAPFFE are that: (1) tax rates may be too aggressive (progressive) for investors to adopt the system; (2) the new tax may end up substituting for the excise tax only, while all other taxes would still apply; (3) it would probably apply to new oil licenses only, leaving a large share of the rent under existing operations untapped; (4) the notion of site is vague; and (5) as a profit-based tax, it gives no incentive for rational resource management and does not rule out profit concealment.

2.13 The new administration has reaffirmed its commitment to some sort of an excess profits tax. The recent governmental strategy plans a "tax on excess income from extraction of hydrocarbons ([in] replacement of the excise tax on petroleum for new deposits and a portion of royalties)." (GOR 2000, 150) The Finance Ministry has confirmed that royalties would be reduced in order to encourage tax compliance. So the excess profits tax would replace mostly royalties instead of excise taxes, as under the TAPFFE proposal.

2.14 Regarding the new differentiated excise tax, rates would vary between RUB 0 and RUB 80 per ton (a return to the old range), as opposed to the currently fixed rate.

2.15 Until these legal provisions become effective, the government will continue to do what it has done since the escalation in oil prices in 1999, which is to rely on export duties for withdrawing part of the rent. Export duties, made flexible to vary with world market prices, are an effective means of capturing the rent, though they discriminate against exports. To the Ministry of Finance they provide the guarantee that oil ownership translates in revenue collection.

2.16 Although taxation is partly to blame for low investments (and thus rent wastage) and low rent capture in the Russian oil sector, changes in taxation alone will not provide the 14
# **1. Introduction**

_“Responding effectively to irregular migration is hampered by a serious lack of verifiably accurate data, making it difficult to identify trends or compare the scale of the phenomenon in different parts of the world.” IOM (2010, p. 31)_ Illegal or irregular migration is a topic of policy interest in much of the world.<sup>1</sup> Globally it is estimated that between 10 and 15 percent of the World’s migrant population, or 20 to 30 million people, are individuals without the appropriate documentation (IOM, 2010). In the United States, it is estimated that 11.2 million people, or 28 percent of all foreign-born (Passel and Cohn, 2011) and 56 percent of all Mexican immigrants (Hanson, 2006) are illegal, while in the European Union estimates range from 7 to 13 percent of the immigrant population (Clandestino, 2009).

However, since illegal migration is by definition migration that occurs without the proper documentation, measuring the extent of it is difficult and the above estimates involve considerable uncertainty. Several approaches are typically used to estimate these stocks. The “residual method” used in the United States involves comparing numbers of individuals recorded as foreign-born in surveys to numbers on official admissions files (Passel and Cohn, 2011). Other estimates come from border apprehension data, re-inspections of travelers, and regularization or amnesty program applications (Morrel-Samuels 2002; IOM, 2010). However, such data are often not available for all countries, and in most cases provide, at best, an estimate of the overall incidence of illegal migration without any socioeconomic or demographic information about these migrants.

An alternative is to try and directly measure illegal migration through survey approaches (Massey and Capoferro, 2007). There are two key challenges here. The first is getting a representative sample of illegal migrants when no sampling frame is available. In countries with high emigration or immigration, a random sample of dwellings might be sufficient. However, in many destination countries where a random sample is not possible, approaches like intercept point sampling may instead need to be used (Clandestino, 2009). The second challenge is

> 1 The terms “illegal immigration”, “irregular migration”, “unauthorized migration”, and “undocumented migration” are often used to describe much of the same phenomena. In some cases it is possible for individuals to be without documents but not technically illegal, but since this is rare, for simplicity we will use the term illegal migration in our paper.

2
Figure 2.4: _However efficient, courts do not have to be necessarily independent_ <!-- Start of picture text --> Legal structure and security of property rights<br>10<br>9 8.2 8.7<br>87 6.5 6.6 6.7 7.0<br>65 3.8 4.0 4.1 4.2 4.6 4.6 4.8 4.9 5.1 5.2 5.4 5.6 5.7 5.8 5.8<br>4<br>3<br>2<br>1<br>0<br>Russia CIS Turkey Ukraine Albania Romania Bulgaria SEE Lithuania Croatia ECA Slovak Rep. Latvia Poland CEE Estonia Czech Rep. Hungary Slovenia Europe US<br><!-- End of picture text --> Source: Economic Freedom of the World, 2003 Annual Report 31