rafmacalaba/datause-encoder-data huggingface dataset:
5. Priori participation of the merged entity in the relevant market or related markets; and 6. Evaluation of possible efficiency gains by the merged firm. Such efficiency gains including economies of scale and scope, significant reduction of administrative costs, transfer of production technology and lowering of production or costs derived from the expansion of an infrastructure or distribution network.

Thus, the merger provisions not only specify that concentration cannot be the sole criteria for determining outcomes, but also provide a list of additional factors to be considered. However, the FECL and Merger Guidelines provide no guidance as to the relative importance of each factor, nor any instructions as to how they ought to be weighted relative to market concentration or market share.

# 2.2 Data Construction

We constructed a dataset from different sources including: the official public resolutions (merger decisions) produced by the FCC and published in the _Gaceta de Competencia Económica_ , Annual Reports and indirect sources, such as specialized magazines.<sup>7</sup> The FCC considered a total of 350 cases covering the period from April 1997 to December 2001. Nevertheless, our dataset includes only those cases having complete information; therefore the final sample contains a total of 239 cases which represent the great majority of horizontal mergers examined by the FCC during this period. Each case file was carefully read by the authors in order to extract and classify the necessary information.<sup>8</sup> 7 An alternative to get accurate information is through the internal files that include the economic report made by the Commission’s staff members. Although we made a formal approach with the Commission’s officials, we were not able to obtain access to such information, as it is classified by law as confidential. Actually, this becomes a restriction to build information on mergers before 1997; the first official publication of merger resolutions was not before April 1997. Coate _et. al._ (1990) were the only scholars able to build data from the internal files of the FTC by agreeing not to publish the data.

8 The complete dataset used in this study is available at: <u>http://www.anahuac.mx/gof/index.php?IDPagina=Avalos%20Brachocv</u> 7
|P035173|2001|2004|5/13/2004|7 Closed|India|
|---|---|---|---|---|---|
|P035173|2001|2005|4/11/2005|9 Closed|India|
|P035173|2001|2006|10/14/2005|10 Closed|India|
|P035173|2001|2006|4/21/2006|11 Closed|India|
|P035173|2001|2006|6/30/2006|12 Closed|India|
|P035311|1999|2001|2/23/2001|5 Closed|Uganda|
|P035311|1999|2002|3/14/2002|7 Closed|Uganda|
|P035311|1999|2003|10/4/2002|8 Closed|Uganda|
|P035311|1999|2004|10/4/2002|8 Closed|Uganda|
|P035312|1996|1996||1 Closed|Trinidad and Tobago|
|P035312|1996|1997||3 Closed|Trinidad and Tobago|
|P035312|1996|1998||6 Closed|Trinidad and Tobago|
|P035312|1996|1999||8 Closed|Trinidad and Tobago|
|P035312|1996|2000|6/23/2000|10 Closed|Trinidad and Tobago|
|P035312|1996|2001|6/11/2001|12 Closed|Trinidad and Tobago|
|P035312|1996|2002|3/28/2002|14 Closed|Trinidad and Tobago|
|P035312|1996|2003|4/17/2003|17 Closed|Trinidad and Tobago|
|P035481|1994|1994||1 Closed|Cameroon|
|P035481|1994|1995||2 Closed|Cameroon|
|P035494|1996|1996||2 Closed|Dominican Republic|
|P035494|1996|1997||4 Closed|Dominican Republic|
|P035494|1996|1998||7 Closed|Dominican Republic|
|P035494|1996|1999||10 Closed|Dominican Republic|
|P035494|1996|2000|6/27/2000|13 Closed|Dominican Republic|
|P035494|1996|2001|3/8/2001|15 Closed|Dominican Republic|
|P035494|1996|2002|6/13/2002|18 Closed|Dominican Republic|
|P035494|1996|2003|3/17/2003|20 Closed|Dominican Republic|
|P035494|1996|2020|7/22/2019|21 Closed|Dominican Republic|
|P035495|1996|1996||2 Closed|Argentina|
|P035495|1996|1997||4 Closed|Argentina|
|P035495|1996|1998||6 Closed|Argentina|
|P035544|1997|1997||0 Closed|Indonesia|
|P035544|1997|1998||3 Closed|Indonesia|
|P035544|1997|1999||6 Closed|Indonesia|
|P035544|1997|2000|4/6/2000|10 Closed|Indonesia|
|P035544|1997|2001|4/4/2001|12 Closed|Indonesia|
|P035590|1994|1994||2 Closed|Mali|
|P035591|1994|1994||2 Closed|Niger|
|P035591|1994|1995||3 Closed|Niger|
|P035592|1994|1994||2 Closed|Senegal|
|P035592|1994|1995||3 Closed|Senegal|
|P035592|1994|1996||4 Closed|Senegal|
|P035593|1994|1994||2 Closed|Burkina Faso|
|P035593|1994|1995||3 Closed|Burkina Faso|
|P035594|1994|1994||2 Closed|Chad|
|P035594|1994|1995||3 Closed|Chad|
|P035595|1995|1995||2 Closed|Gabon|
|P043195|2004|2006|11/10/2005|8 Closed|Croatia|
|---|---|---|---|---|---|
|P043195|2004|2006|4/4/2006|9 Closed|Croatia|
|P043195|2004|2007|10/31/2006|10 Closed|Croatia|
|P043195|2004|2007|3/30/2007|11 Closed|Croatia|
|P043195|2004|2008|10/10/2007|12 Closed|Croatia|
|P043195|2004|2008|5/30/2008|13 Closed|Croatia|
|P043195|2004|2009|11/4/2008|14 Closed|Croatia|
|P043195|2004|2010|8/3/2009|15 Closed|Croatia|
|P043195|2004|2010|12/16/2009|16 Closed|Croatia|
|P043195|2004|2010|6/18/2010|17 Closed|Croatia|
|P043195|2004|2011|2/12/2011|18 Closed|Croatia|
|P043195|2004|2011|6/26/2011|19 Closed|Croatia|
|P043195|2004|2012|12/18/2011|20 Closed|Croatia|
|P043195|2004|2013|9/26/2012|21 Closed|Croatia|
|P043231|1996|1996||1 Closed|Tajikistan|
|P043231|1996|1997||3 Closed|Tajikistan|
|P043231|1996|1998||4 Closed|Tajikistan|
|P043231|1996|1999||6 Closed|Tajikistan|
|P043231|1996|2000|6/29/2000|8 Closed|Tajikistan|
|P043231|1996|2020|3/12/2020|1 Closed|Tajikistan|
|P043254|2002|2002|6/27/2002|1 Closed|Yemen,Republic of|
|P043254|2002|2003|6/30/2003|4 Closed|Yemen,Republic of|
|P043254|2002|2004|4/28/2004|6 Closed|Yemen,Republic of|
|P043254|2002|2005|4/17/2005|9 Closed|Yemen,Republic of|
|P043254|2002|2006|8/7/2005|10 Closed|Yemen,Republic of|
|P043254|2002|2006|11/17/2005|11 Closed|Yemen,Republic of|
|P043254|2002|2006|5/3/2006|12 Closed|Yemen,Republic of|
|P043254|2002|2006|6/29/2006|13 Closed|Yemen,Republic of|
|P043254|2002|2006|6/30/2006|14 Closed|Yemen,Republic of|
|P043254|2002|2007|12/27/2006|15 Closed|Yemen,Republic of|
|P043254|2002|2007|6/27/2007|16 Closed|Yemen,Republic of|
|P043254|2002|2008|12/28/2007|17 Closed|Yemen,Republic of|
|P043254|2002|2008|6/21/2008|18 Closed|Yemen,Republic of|
|P043254|2002|2009|12/31/2008|19 Closed|Yemen,Republic of|
|P043254|2002|2009|6/13/2009|20 Closed|Yemen,Republic of|
|P043254|2002|2010|6/13/2009|20 Closed|Yemen,Republic of|
|P043255|2001|2001|6/20/2001|2 Closed|Yemen,Republic of|
|P043255|2001|2002|5/16/2002|4 Closed|Yemen,Republic of|
|P043255|2001|2003|6/30/2003|7 Closed|Yemen,Republic of|
|P043255|2001|2004|5/10/2004|9 Closed|Yemen,Republic of|
|P043255|2001|2005|4/29/2005|11 Closed|Yemen,Republic of|
|P043255|2001|2006|12/19/2005|12 Closed|Yemen,Republic of|
|P043255|2001|2007|11/19/2006|13 Closed|Yemen,Republic of|
|P043255|2001|2007|6/19/2007|14 Closed|Yemen,Republic of|
|P043310|1996|1996||2 Closed|India|
|P043310|1996|1997||5 Closed|India|
|P043310|1996|1998||9 Closed|India|
# **Climate change and trade policy: From mutual destruction to mutual support***

Patrick A. Messerlin Groupe d’Economie Mondiale de SciencesPo Paris

**Keywords:** trade liberalization, WTO, national treatment, most-favored nation, carbon border tax adjustment, carbon tariffs, carbon conditional measures, carbon policies.

**JEL codes:** F13, F18, F5, Q54, Q56, Q58.

This paper is a contribution to the DFID-World Bank Global Trade and Finance Architecture project. It is based on a presentation made at the Séminaire de la Chaire Développement Durable, Ecole Polytechnique et Sciences Po, 20 December 2009. I would like to thank very much Claude Henry for inducing me to work on this issue, and Olivier Cattaneo, Jim de Melo, Julien Hanoteau, Bernard Hoekman, Petros Mavroidis, Michael Moore, Joost Pauwelyn and the participants of the Séminaire for very useful comments and discussions.

1
|Sugar|-29.2|-25.3|-21.4|-17.4|-11.3|-104.6|-31.4|
|---|---|---|---|---|---|---|---|
|Tea|-8.2|-7.2|-6.1|-4.6|-3.0|-29.1|-8.7|
|Macaroni|-32.3|-26.9|-22.6|-17.9|-12.0|-111.7|-33.5|
|Vegetable Oil|-70.7|-59.3|-50.9|-40.2|-27.1|-248.3|-74.5|
|Paste tomatoes|-26.1|-22.1|-18.7|-14.7|-9.9|-91.4|-27.4|
|Milk for<br>children|-2.9|-4.3|-5.2|-6.1|-5.7|-24.2|-7.3|
|Milk<br>(concentrated)|-17.6|-15.8|-13.1|-9.7|-6.4|-62.6|-18.8|
|Total|-348.0|-305.6|-264.1|-213.8|-151.6|-1,283.0|-384.9|

Source: Libyan Household Consumption Survey 2007/8; Libyan authorities; and Bank staff calculations.

**Table 12: Per-capita Impact of Subsidy Reform (% of per-capita expenditure)**

||**Q1**|**Q2**|**Q3**|**Q4**|**Q5**|**Total**<br>**scenario 2**|**Total**<br>**scenario 1**|
|---|---|---|---|---|---|---|---|
|Flour|-1.37|-0.92|-0.71|-0.55|-0.31|-0.71|-0.21|
|Flour-bread|-4.85|-3.61|-2.78|-2.18|-1.54|-2.80|-0.84|
|Semolina|-0.22|-0.15|-0.10|-0.07|-0.03|-0.11|-0.03|
|Rice|-2.30|-1.63|-1.28|-0.97|-0.59|-1.26|-0.38|
|Sugar|-1.59|-1.10|-0.83|-0.63|-0.37|-0.83|-0.25|
|Tea|-0.44|-0.32|-0.24|-0.17|-0.10|-0.23|-0.07|
|Macaroni|-1.75|-1.18|-0.88|-0.65|-0.39|-0.89|-0.27|
|Vegetable Oil|-3.84|-2.59|-1.97|-1.46|-0.88|-1.98|-0.59|
|Paste tomatoes|-1.42|-0.96|-0.73|-0.53|-0.32|-0.73|-0.22|
|Milk for children|-0.16|-0.19|-0.20|-0.22|-0.18|-0.19|-0.06|
|Milk (concentrated)|-0.96|-0.69|-0.51|-0.35|-0.21|-0.50|-0.15|
|Total|-18.89|-13.35|-10.23|-7.79|-4.93|-10.24|-3.07|

Source: Libyan Household Consumption Survey 2007/8; Libyan authorities; and Bank staff calculations.

The direct impact on government expenditure from the complete removal of subsidies (Scenario 2) would be equivalent to the total impact on household welfare, namely 1.3 billion LYD—equivalent to 2.8% of government expenditure (Table 13, last two columns).<sup>15</sup> However, under a partial reduction of subsidies (30% in the case of scenario 1), the total impact on government expenditure would be greater than the impact on household welfare (Table 13, upper 6 lines). Under scenario 1, the former would amount to 660 million LYD, compared to 385 million LYD for the impact on household welfare (Table 11). This difference is explained by the fact that - when subsidies are not totally removed - we have two potential causes for lower government expenditure, the first resulting from the increase in subsidized prices (which is equivalent in size to the impact on household welfare) and the second resulting from the reduction in quantities consumed by households at these higher subsidized prices. If subsidies were totally eliminated, this second effect would disappear given that no quantities would be sold at a subsidized price.

> 15 Estimates of the budgetary impact of alternative reform scenarios do not take into account savings from lower administrative costs of managing the subsidy program and from leakages of the subsidy program (e.g. smuggling).

15
characteristics we have access to does not seem to influence the program effect, this is subject to change in a setting where more variables are available.

Notably, the enhanced effectiveness in lower-value properties prompts a discussion on algorithmbased taxation strategies, which, while aiming to improve compliance, could inadvertently focus enforcement on lower-income owners, potentially leading to regressive taxation. This underscores the need for further research on algorithm-based taxation and policy learning as a natural progression from this study.

# **References**

- Advani, A., Elming, W., & Shaw, J. (2023). The dynamic effects of tax audits. _The Review of Economics and Statistics_ , _105_ (3), 545–561. https://doi.org/https://doi.org/10.1162/rest_a_ 01101

- Allingham, M., & Sandmo, A. (1972). Income tax evasion: A theoretical analysis [cited By 2152]. _Journal of Public Economics_ , _1_ (3-4), 323–338. https://doi.org/10.1016/0047-2727(72) 900102

- Asatryan, Z., & Peichl, A. (2017). Responses of firms to tax, administrative and accounting rules: Evidence from armenia [cited By 9]. _Responses of firms to tax, administrative and accounting rules: Evidence from Armenia_ .

- Athey, S., & Imbens, G. (2016). Recursive partitioning for heterogeneous causal effects. _Proceedings of the National Academy of Sciences_ , _113_ (27), 7353–7360. https://doi.org/10.1073/ pnas.1510489113

- Athey, S., & Imbens, G. W. (2019). Machine learning methods that economists should know about. _Annual Review of Economics_ , _11_ (Volume 11, 2019), 685–725. https: // doi. org / https://doi.org/10.1146/annurev-economics-080217-053433

- Athey, S., & Wager, S. (2019). Estimating treatment effects with causal forests: An application. _Observational  Studies_ , _5_ (2),  37–51.  https://doi.org/10.1353/obs.2019.0001

25
# **Dollarization Dilemma: Price Stability at the Cost of External Competitiveness in Cambodia**<sup>*****</sup>

Sovannroeun Samreth,<sup>†</sup> Miguel Eduardo Sánchez-Martín,<sup>‡</sup> and Sodeth Ly<sup>§</sup>

## JEL Classification:

E5 Monetary Policy, Central Banking, and the Supply of Money and Credit

- F31 Foreign Exchange

- O24 Trade Policy • Factor Movement Policy • Foreign Exchange Policy

> *  The authors are grateful to Charl Jooste, Naoko Kojo and Deepak Mishra for the insightful comments shared on previous versions of this paper, as well as the National Bank of Cambodia for providing necessary data for this research. Any error in this paper is the responsibility of the authors. † Graduate School of Humanities and Social Science, Saitama University, Japan.

> ‡ Senior Economist in the Macroeconomics, Trade and Investment global practice, the World Bank Group.

> § Senior Economist in the Macroeconomics, Trade and Investment global practice, the World Bank Group.
2011) and Ecuador (Calero, Bedi, and Sparrow 2009).

# **5 Financial capital and entrepreneurship**

Temporary migration is also linked to increased investment and entrepreneurship back in the home country. While there are studies on the increase in investment in assets, such as land in Pakistan (Adams Jr 1998) and El Salvador (Damon 2010), most papers focus on the link between temporary migration and entrepreneurship. Seeking self-employment and entrepreneurship opportunities after return has been argued to be among the main drivers of temporary migration: in the presence of credit constraints at home, temporary migration allows individuals to accumulate savings faster and to engage in self-employment activities when they return (Dustmann and Kirchkamp 2002; Rapoport 2002; Djaji ́c 2010; Bossavie, Gorlach, Ozden, and Wang 2021). This motive is especially relevant in developing economies where credit constraints to entrepreneurship can be quite restrictive. Temporary migration can thus allow to overcome the institutional void of missing capital markets in origin countries to accelerate business creation (Bossavie, Gorlach, Ozden, and Wang 2022).

Empirical evidence from various countries is consistent with the entrepreneurship channel. A first set of descriptive studies examine the relationship between temporary migration and self-employment after return. Savings levels have been found to be a significant factor in the choice of self-employment over waged employment among return migrants in Pakistan (Ilahi 1999) and Egypt (McCormick and Wahba 2001). In Tunisia, the majority of entrepreneurial projects started by returnees were totally financed through overseas savings (Mesnard et al. 2004). In Turkey, more than half of returnees from Germany are economically active and engaged in entrepreneurial activities (Dustmann and Kirchkamp 2002).<sup>17</sup> Using historical data on return migrants to Norway from the United States, Abramitzky, Boustan, and Eriksson (2019) also show that return migrants to rural Norway back in the late 1800s and early 1900s were more likely to become owner occupier farmers although they came from poorer backgrounds than non-migrants. Similarly, return migrants have been found to be more likely to become entrepreneurs than non-migrants, after accounting for selection in emigration and return migration in Albania (Piracha and Vadean 2010) and Egypt (Mah ́e 2019; Wahba and Zenou 2012; Wahba 2015). A causal relationship between temporary migration and financial investment back home has been estimated using natural experiments in the Philippines (Yang 2006; Yang 2008; Khanna, Theoharides, and Yang 2020), Mexico (Woodruff and Zenteno 2007) and Mozambique (Batista, McIndoe-Calder, and Vicente

> 17Consistent with this evidence, an analysis of a sample of workers from seven developing economies by Giambra and McKenzie (2021) finds that self-employed individuals are also less likely to emigrate.

27
8 effort on their part.<sup>5</sup> Legislators must identify multiple small or mid-size projects because of size limits on any one project; they also need to negotiate implementation with local bureaucrats, who have considerable power either to reject the project on grounds of nonconformity with project guidelines or to stall its implementation.<sup>6</sup> Two pieces of evidence further support the argument that MPLADS disbursement requires legislators to exert effort. First, the report of the MPLADS audit conducted by the Comptroller and Auditor General, covering the period 1997-2000, showed that only 40 percent of projects recommended by MPs were subsequently sanctioned by District Commissioners (the top public officials in every district, an administrative unit in India that does not necessarily correspond to electoral constituencies), taken up by implementing agencies and completed.<sup>7</sup> Actual spending under MPLADS is a close approximation of project execution because the money is released against the issuance of completion certificates by the implementing agents.<sup>8</sup> 5 The implementation procedures are available at the following web-site: http://mplads.nic.in/dpguid.htm 6 A telling anecdote on the challenges of getting projects implemented through local bureaucracies is provided in a study of MPLADS undertaken by the Planning Commission of India (2001). An MP from the state of Kerala recommended construction of additional classrooms to a rural high school on November 11, 1996. The concerned District Collector (DC) took 38 days to review and forward this proposal for estimate preparation to the relevant Block Development Officer (BDO). The BDO took 46 days to prepare the estimate and forward it to the District Rural Development Agency (DRADA) for approval. The DRDA provided its approval after 130 days. It then took the DC 250 days to formally provide administrative sanction to the work. The Block Level Beneficiary Committee which had to execute the work (because the Guidelines prohibit using professional contractors for MPLADS works) was constituted 220 days after the DC had sanctioned the work, by which time they declared the work could not be undertaken because the funds allotted were insufficient.

7 MPLADS expenditures were last audited in 2000, covering the period 1997-2000 and 241 out of 786 constituencies. The audit was critical and has not been repeated. See <u>http://cag.nic.in/html/reports/civil/2001_book3a/index.htm</u> 8 Although the audit report points to some irregularities in this, with money being released without proper collection of completion certificates, and even with such certificates it is possible that the money was diverted to things other than the intended works, getting their allocations recorded as
evidence of an effect of market power on the dependent variable, and our previous results regarding the effect of preferential liberalization and TTBs still hold.<sup>46</sup> One potential and likely contributing explanation behind the weakness of our results linking any influence of import market power to changes in external tariffs is due to our poor measures of import market power, which may simply be ill-suited to this particular application. Given the necessity for our exercise to utilize the tariff data from the early 1990s, in order to match the Estevadeordal et al. (2008) approach, the analysis had to be conducted at the relatively aggregated ISIC 4-digit level. As we have noted, measurement error for the elasticities is a generally recognized problem, and we have attempted to address it through a variety of standard techniques. Nevertheless, in this particular setting, it may simply be that the measurement error may have been compounded given that the elasticity estimates were constructed from a slightly later time period and given the need to concord elasticity estimates from the 6-digit HS to 4-digit ISIC level. Future work utilizing different, and perhaps more disaggregated data and potentially improved measures of elasticities may be a promising avenue to pursue, given the richness of the policy variation in the underlying setting.<sup>47</sup> Nevertheless, a separate and important potential explanation that we also cannot rule out, and which is supported by the broader patterns in the underlying data, is that Argentina and Brazil did not exploit their market power after formation of the customs union because, institutionally, _de facto_ there was no customs union. Given that each country pursued its TTB policies independently, easy access to this “escape clause” may have resulted in both Argentina and Brazil being unable to exploit any of their joint market power by raising their (joint) levels of import protection toward PTA outsiders in concert. Put differently, market power may be more likely to matter if Argentina and Brazil had been committed to actually changing the common external MFN tariff jointly or by coordinating their antidumping and safeguards policies jointly against non-members. The MERCOSUR institutional framework certainly did not require TTB coordination to occur, and the result is that these countries’ TTB policy applications were clearly not coordinated in practice (see again Section 2).

> 46 Those results are not shown but are available on request.

> 47 See, in particular, the methodological advancements for estimating elasticities proposed by Soderberry (2015) and his application for estimates for the United States.

28
**Figure 5. Politically Connected vs Non-Connected Firms (percent, relative to non-connected firms)**

<!-- Start of picture text --> 40<br>20<br>0<br>-20<br>-40<br>-60<br>-80<br>Turnover Employment Effective tax rate Productivity (TFP)<br>(p.p.)<br>Approach 1 Approach 2<br><!-- End of picture text --> Politically-connected firms are also less profitable. Firms identified using Approach 1 have 1.6 percentage points lower probability of being profitable than non-connected firms. Firms identified using Approach 2 have 20.7 percentage points lower probability of being profitable.<sup>18</sup> Not surprisingly, politically-connected firms tend to have lower return on assets and equity. Return on assets is lower by 2.7 to 8 percentage points, while return on equity is lower by 6.6 to 7 percentage points. The potential reasons for lower profitability could be aggressive tax planning and shifting of the profits to other jurisdictions. Recent work of Balabushko, Beer, Loeprick and Vallada finds direct revenue losses linked to treaty restrictions on taxing rights, especially for flows into a few major investment hubs.

**Figure 6. Connected firms are less profitable (percentage points, relative to non-connected firms)**

<!-- Start of picture text --> 0<br>-5<br>-10<br>-15<br>-20<br>-25<br>Probability of Return on assets Return on equity<br>profitability<br>Approach 1 Approach 2<br><!-- End of picture text --> 17 Numbers in the write-up could differ from the regression coefficients due to coefficient interpretation issues. For example, given case is log-lin, so interpretation is the following: exp(0.085)=1.089. 18 Probability of connected: log(0.29-0.065)/(1+ log(0.29-0.065))=55.6 percent. Probability of non-connected is log(0.29)/(1+ log(0.29))=57.2 percent. The difference Is 1.6 percentage points.

10