rafmacalaba/datause-encoder-data huggingface dataset:
Independently from whether the Andean safeguards are included in the calculation or not, Colombia’s experience differs from the international trend regarding the adoption of this type of measures vis-a-vis anti-dumping duties. According to Finger (2002), between 1983 and 1993, an annual average of 3 safeguard measures was reported to the GATT, in accordance with Article XIX of the Agreement, while the yearly average of dumping cases was 164. While the worldwide statistic is one safeguard case for every 55 cases of dumping per year, for Colombia the figure is almost 1 to 1.<sup>17</sup>

**Chart III.1**

## **INVESTIGATIONS CONDUCTED**

1990-2004

|Type of Investigation|Numb|er of Investigati|ons||Percentages||No<br>imposition/|In<br>process/|
|---|---|---|---|---|---|---|---|---|
||Conducted|No duties or<br>measures<br>imposed|In<br>process|Conducted|No<br>imposition|In<br>process|Conducted|Conducte<br>d|
|Dumping|37|14|4|52.1|60.9|44.4|37.8|10.8|
|Safeguard<sup>1/</sup>|34|9|5|47.9|39.1|55.6|26.5|14.7|
|WTO|11|1|2|15.5|4.3|22.2|9.1|18.2|
|_Special safeguard_|10|5|2|14.1|21.7|22.2|50.0|20.0|
|Andean|12|3|0|16.9|13.0|0.0|25.0|0.0|
|AEC 24|1|0|1|1.4|0.0|11.1|0.0|100.0|
|**TOTAL**|**71**|**23**|**9**|**100.0**|**100.0**|**100.0**|**32.4**|**12.7**|

1/ The information on safeguards is broken down in accordance with the existing legislation, Decree 152/98 for WTO member countries; Decree 1407/99 for all the so-called special safeguard countries; Andean rules; ACE 24, which is the Agreement between Colombia and Chile within the framework of ALADI, using ALADI ́s Resolution No. 70.

Source: Calculated by the authors based on Ministry of Trade data.

# **_A. Evolution of investigations 1990-2004_**

Between 1990 and 2004 there have been a total of 71 dumping and safeguard related investigations in Colombia. Of these, 37 are dumping investigations and 34 are safeguard

> 17 Finger, J.M. (2002), “Safeguards: Making sense of GATT/WTO provisions allowing for import restrictions” in Development, Trade and the WTO: a Handbook, Bernard Hoekman, Aaditya Mattoo and Philip English eds., World Bank.

20
_COTE D’IVOIRE: Volatility, Shocks and Growth_

# **IBLIOGRAPHY**

Bogetic, Zeljko and Carlos Espina, and John Noer (2007a).“COTE: D’IVOIRE: From Success to Failure––A Story of Growth, Specialization and the Terms of Trade”, _World Bank Policy Research Paper_ , forthcoming.

Bogetic, Zeljko and Carlos Espina, and John Noer (2007b).“COTE: D’IVOIRE: “Competitiveness, Cocoa and the Real Exchange Rates”, _World Bank Policy Research Paper_ , forthcoming.

Cashin, P., L. Céspedes and R. Sahay (2002) “Keynes, Cocoa And Copper: In Search Of Commodity Currencies”.INTERNATIONAL MONETARY FUND SEMINAR SERIES (INTERNATIONAL); No. 2002-76:1-49.

Cashin, Paul, 2003. _Commodity Prices and the Terms of Trade_ . In IMF Research Bulletin, Volume 4, Number 4, International Monetary Fund.

Edwards, Sebastian. _Real Exchange Rates in Developing Countries: Concepts and Measurement_ , NBER Working Paper series No. 2950, April 1989 Hansen, B. E. and P. C. B. Phillips (1990), "Estimation and Inference in Models of Cointegration: A Simulation Study", Advances in Econometrics, Vol. 8, pp. 225-248, Jai Press, Inc.:London.

Hansen, B. (1992) “Tests for Parameter Instability in Regressions with I(1) Processes”. Journal of Business and Economic Statistics. Vol. 10, No. 3.

Hodrick, Robert J. and Edward C. Prescott, "Postwar U.S. Business Cycles: An Empirical Investigation," _Journal of Money, Credit, and Banking_ 29 (1), February 1997, pp. 1-16.

McIntire, John and Panos Varangis (1999). “Reforming Cote d’Ivoire’s Marketing and Pricing System,” World Bank PR Working Paper No. 2081.

Phillips, P.C.B and B. Hansen (1990) “Statistical Inference In Instrumental Variables Regression With I(1) Processes”. REVIEW OF ECONOMIC STUDIES (U.K.); 57:99125.
_COTE D’IVOIRE: Volatility, Shocks and Growth_

**(depreciates) to about +0.4% two years out, then oscillating downward again.** The oscillation and the response of the bilateral RER is less pronounced than that of the terms of trade. The particular measure of the real exchange rate used here is built with the consumer price indices of France and Cote d’Ivoire respectively, and the (fixed) official exchange rate. The Ivoirian CPI appears in the denominator, and raw cocoa prices do not appear directly anywhere in this measure. (There is probably a very small share for chocolate in the CPIs and hence in the measure.). This response may be the result of a “wealth effect”. A high cocoa price raises Cote d’Ivoire wages and incomes, bidding up the local price level relative to that of France, resulting in a loss of competitiveness and a dip (appreciation) in the real exchange rate measure. This explanation is also consistent with a time lag in the transmission of the effect. The oscillation seems to be related and inverse to the oscillation in the terms of trade.

**Figure 9:  Vector Auto Regression Impulse Response Functions: Impacts of a Shock of World Cocoa Prices on Cote d’Ivoire’s Terms of Trade, Real Exchange Rate, and Real GDP per Worker**

<!-- Start of picture text --> VAR Impulse Response Graphs: Impact of Shocks to Cocoa Prices<br>upon The Real Exchange Rate, Terms of Trade, and GDP per Worker<br>0.05<br>RER Response<br>0.04<br>TOT Response<br>GDP per worker response<br>0.03<br>0.02<br>0.01<br>0<br>0 1 2 3 4 5 6 7<br>-0.01<br>Step<br>-0.02<br>-0.03<br>-0.04<br><!-- End of picture text -->

**Shocks to cocoa prices have an immediate positive small impact upon GDP per worker.** This impact continues to about plus-one-half-percent one year out, and then increases  to about one percent two years out. The impact thereupon diminishes.

**Overall, the VAR statistical evidence is that shocks to real world cocoa prices have a direct effect on Cote d’Ivoire’s output, and an even stronger impact on two important measures of the country’s trade environment.** The total impact includes the direct impact on GDP plus the indirect impact via trade. Also, one-time cocoa price shocks are associated with wave-like oscillations in these variables, especially the trade indicators. The real exchange rate and terms of trade have a big impact on productivity in
database as a source of firm-level data for the cross-listing firms. I find that country-level characteristics like size and liquidity of the home country’s market and the extent of legal rules and investor protection are significant predictors of a control change to domestic owners. In contrast, individual firm characteristics, such as size, leverage and market valuation are important predictors of control change to foreign owners. Additional tests show that capital control regulations and FDI restrictions in the home country decrease the probability of control changes to foreign shareholders.

Post-listing characteristics of firms that cross-list show that all firms have significantly higher foreign income growth rates. So an ADR listing is able to expand the international orientation of the foreign firms. I also find that firms that undergo control changes, especially to foreign owners significantly increase their leverage ratios.

In summary, the paper shows that the increased regulation associated with US markets is not effective enough in changing the ownership concentration of foreign firms that cross-list on US exchanges. The feature of the US corporate law system that limits private benefits of control doesn’t produce an increase in dispersed ownership structures in firms issuing an ADR. However, cross-listing does provide an opportunity for existing shareholders to sell out to new owners as evidenced by the high incidence of control transfers in the study sample. The evidence suggests that rather than bonding there The paper is organized as follows. Section 2 examines related literature and discusses the main hypothesis this paper tests. Section 3 discusses the data and summary statistics. Section 4 presents the main results. Section 5 concludes with implications for future research.

# 2. Motivation and Related Literature

In this section I identify the different ways in which foreign companies can approach the US markets and the reasons for them to do so. Section 2.1 discusses what an American 4
# **I. Introduction**

Since the beginning of the 1990s, Bangladesh has witnessed robust economic growth, relatively stable inequality and consequently respectable rates of poverty reduction. The proportion of poor in 1990 was 59%, ten years later it had declined to 49% and by 2005, due to a faster pace of poverty reduction, the headcount rate fell to 40% (World Bank 2008). In this paper we analyze the factors that contributed to the substantial decline in poverty between 2000 and 2005 and compare it to what we know about the drivers of poverty reduction in earlier decades. Specifically we analyze the determinants of poverty using nationally representative household data from two different points in time (2000 and 2005), examining the extent to which poverty reduction is explained by changes in attributes of households (including household and geographic factors) and changes in the returns to these attributes. We use the same decomposition methodology as Wodon (1999), who used earlier rounds of the same dataset to assess the factors explaining poverty reduction in Bangladesh between 1983/84-1995/96, in order to assess changes in the micro-determinants of growth and poverty reduction over time.

A specific question in this context relates to the role of geographic location in determining the economic status of households. Wodon (1999) and Ravallion and Wodon (1999), using survey data from 1988 and 1992, had found a significant and sizable geographic effect on poverty in Bangladesh, with the most significant (and positive) impact arising from the location of a household in the greater Dhaka region. In other words, even after controlling for mobile characteristics of households, location of a household in the region surrounding the capital city of Dhaka had a positive and significant effect on household consumption, relative to being located outside this region.

2
which corresponds to the agreed definition of ‘climate’) averages, or to the cumulative effect of many repeated weather events driven by an increase in frequency linked to climate change. There are some promising approaches in the literature in this respect. For example, Cattaneo and Peri employ a technique which is now quite common in the new weather-economy literature (Dell, Jones and Olken, 2014; Burke and Emerick, 2016; Liu et al., 2022) called ‘longdifferences’. This approach consists of replacing annual averages of both the dependent and independent (climatic) variables of interest with decadal or multi-decadal averages of the same. This allows one to test whether the short-run relationships retrieved using annual measures also hold in the medium- and long-run, thus directly testing the external validity of the empirical findings in a climate change perspective. Cattaneo and Peri (2016) cleverly use long-differences to confirm their short-run result that warming in poor countries reduces migration (consistently with the presence of severe liquidity constraints) and find evidence in support of the persistence of this type of effect.

- <mark>As explained in the previous subsection, it is now well established that the causal link between the two phenomena is not as simple and straightforward as it once seemed to be, and there are many intervening factors (liquidity constraints, assets,</mark> _<mark>in situ</mark>_ <mark>adaptation strategies such as irrigation or other on-farm investments, etc.) that have the power to alter not just the magnitude, but even the sign of the relationship. Once the analyst retrieves a statistically significant relationship between a climate shock and the decision to migrate, how can the effect be explained in light of the above-mentioned mechanisms? Recent advances in empirical micro-econometrics, such as, in particular, mediation analysis to investigate the mediating role of a variable of interest (the so-called ‘mediator’) in explaining a causal relationship of interest appear promising, although not yet picked up by scholars in the migration field.</mark><sup>7</sup> <mark>The analysis of migration-asadaptation, i.e., of how the decision (not) to migrate fits within a broader analytical framework on the full pool of adaptation options available to farmers in response to climate change, is also still underexplored. I</mark> n this respect, while the ‘rare event’ nature of migratory flows is a drawback for household surveys, the potential to carry out empirical analyses of the full range of intervening factors, mediating channels, and adaptation options available to households in response to

> 7 Recent examples of works leveraging the potential of this methodology to unpack the black box of causal relationships in the development field are Azzarri et al. (2022), Pace et al. (2022), and Prifti, Daidone, and Davis (2019). For a comprehensive review of the use of mediation analysis in economics, see Celli (2021).

17
8 done at the International Monetary Fund by Ian McCarthy in 1979. More recently, Charles W. Colomiris has done a survey of pre-FDIC regional deposit insurance systems in the United States. 6 Also, within the context of broader surveys of financial regulation and supervision, R.M. Pecchioli and Richard Dale reviewed deposit insurance systems for O.E.C.D. countries and the Group of Thirry countries. 7

# II. ANALYSIS AND EVALUATION OF DEPOSIT INSURANCE

As indicated earlier, we believe that the most useful way to analyze and evaluate deposit insurance systems is to compare them with the implicit deposit protection schemes that typically are employed in developing countries without deposit insurance. In order to compare these two systems, it is necessary to specify the major features of implicit and explicit systems. It is important to emphasize that in actual practice implicit and explicit systems do not take the same form in every country. Consequently, it is necessary to generalize their basic features. We believe that these generalizations constitute a satisfactory basis for reaching conclusions regarding the pros and cons of the two systems. Of course, in evaluating the two systems in a given country, policymakers should identify the specific features of the two systems in that country, and then use these features to compare the systems.

3 Ian S. McCarthy, 'Deposit Insurance: Theory anid Practice", International Monetary Fund, Staff Papers, September 1980, pp. 578-600.

6 Charles W. Colomiris, 'Deposit Insurance: Lessons from the Record", Economic Perspective, Federal Reserve Bank of Chicago, May/June 1989, pp 10-30.

7 R.M. Pecchioli, Prudential SuRervision in Banking, 1987, pp. 133-48; and Richard Dale, The Regulation of International Banking, 1987, pp. 141-55.
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Kraft, M. A., and D. Blazar. 2016. “Individualized Coaching to Improve Teacher Practice Across Grades and Subjects: New Experimental Evidence.” Educational Policy (advance online publication). http://journals.sagepub.com/doi/abs/10.1177/0895904816631099.

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35
on a newborn's current and future health cannot be approximated well by the cost of a few pre- and post-natal visits. Unit costs may also be very hard to calculate exactly. For example, unit costs of inpatient hospital visits will differ widely according to the illness being treated. They will also be badly estimated if there is rent-seeking including, for example, the funneling of benefits away from households. Finally, the approach assumes that publicly-provided services are homogeneous across all consumers. Yet, quality may vary enormously and imply higher benefits to certain households and lower ones to others.

With expanding access to improved and more detailed data sets, some of these problems are being tackled. Various papers in PSP demonstrate some of the corrections and innovations that can be made to improve the benefit-incidence approach. Many of the method's deficiencies have more to do with data inadequacies than with limitations intrinsic to the approach and are thus shared with other methodologies. For example, there is nothing in the traditional benefit-incidence methodology which prevents the incorporation of quality differentials. As elsewhere, the major impediment stems from the deficiencies of available data.

What policy conclusions can we draw from such exercises? Although the methodology is far from ideal, and so precise magnitudes may not be correct, it is generally assumed that the broad qualitative conclusions are indicative of reality. We still know rather little about how much difference behavioral responses can make to key policy conclusions. Nonetheless, even a crude but careful incidence study can be valuable to governments, who often have little or no awareness of the possible distributional implications of their policies, and to policymakers generally. The issue of how public spending benefits are distributed is an important one and incidence analysis appears to provide a useful first approximation. I shall attempt to summarize some of the results to have emerged later.

8
# **5 Quantitative Analysis**

In this section, I present the quantitative analysis of the model. Subsection 5.1 presents the benchmark calibration. Subsection 5.2 presents key statistics in the data and model simulations. Subsection 5.3 inspects the mechanism of the model. Subsection 5.4 explores the social welfare implications of having an independent central bank that can accumulate international reserves.

## **5.1 Calibration**

**Functional Forms.** —The utility function with constant relative risk aversion is given by

with _σ_ = 1, and I follow Chatterjee and Eyingungor (2012) by adopting the functional form for default costs given by

**Parameter Values.** —The model is solved numerically to evaluate its quantitative predictions regarding the level of international reserves, public debt, and sovereign spreads. The appendix describes the computation of the model. I calibrate the model using data for Mexico from 1994 to 2017, a typical emerging economy with an independent central bank used commonly as a reference for studies on reserves accumulation.<sup>28</sup> A period in the model refers to a year. I choose a subset of parameter values (summarized in table 2) that can be directly pinned down from the data, and then I choose a second subset of parameter values (summarized in table 3) such that model simulations match key aspects of the data.

The risk aversion parameter value ( _σ_ = 2) is standard in quantitative business cycle and sovereign default studies. The international risk-free interest rate is set to match the average real interest rate for US Treasury Bills from 1980 to 2017, which is set to 1 _._ 1% ( _r_<sup>_∗_</sup> = 0 _._ 011). I use spreads from the EMBI+ to parameterize the lenders’ stochastic discount factor. I assume that a period with high risk aversion is one in which the global EMBI+ is one standard deviation above the median over the sample period. With this procedure, I obtain 6 episodes of high risk premium every 20 28The time period starts in 1994 because the Mexican central bank independence reform was approved in 1993.

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