rafmacalaba/datause-encoder-data huggingface dataset:
# **<u>TABLE 4: The optimal toll and efficiencies captured by the toll on delay only</u>**

||**2002**<br>**Base**|**Optimal toll on**<br>**excess delay and**<br>**excess fuel**<br>(0.486<br>/<br>.<br>.<br>6.679<br>/<br>)<br>_BRL pass km_<br>_or_<br>_BRL liter_|**Toll on excess**<br>**delay only**<br>(0.288<br>/<br>.<br>.<br>3.723<br>/<br>)<br>_BRL pass km_<br>_or_<br>_BRL liter_|**Percent of**<br>**optimal change**<br>**from base captured**<br>**by toll on delay only**|
|---|---|---|---|---|
|Speed (km/hr)|24.10|51.27|39.89|58.1|
|Auto person trips<br>6<br>( 10 )<br>|5.6745|2.2096|3.3528|67.0|
|Bus person trips<br>6<br>( 10 )<br>|5.8861|9.0790|7.9720|65.0|
|Auto vehicle kil.<br>8<br>( 10 )<br>|1.1761|0.4580|0.6949|67.0|
|Auto hours<br>6<br>( 10 )<br>|4.8801|0.8933|1.7423|78.7|
|Auto fuel (liters)<br>7<br>( 10 )<br><br>|1.1431|0.3331|0.5371|74.6|
|Auto CO2mill. tons/year|5.8330|1.6997|2.7407|74.6|
|Car equiv. traffic<br>6<br>( 10 )<br><br>|<sup>3.5577</sup>|1.7487|2.3427|67.2|
|Fuelcost/trip (BRL)|1.7272|1.2928|1.3735|81.4|
|Toll/trip (BRL)|0|10.07|5.9636|59.2|
|Consumersurplus/trip|6.9595|7.2217|7.1459|71.1|
|_f_=1|2.5979|2.3469|2.3819|86.0|
|_f_=2|3.8817|3.6057|3.6345|89.5|
|_f_=3|5.8834|5.5607|5.5977|88.5|
|_f_=4|9.7969|9.8001|9.8151|105.7|
|_f_=5|15.4063|17.5192|17.1637|83.2|
|_f_=6|22.3769|30.4549|28.3891|74.4|
|Socialwelfare./trip|6.9595|8.3728|8.1803|86.4|
|Revenue /day<br>7<br>( 10 )<br>|0|2.2251|1.9995|89.9|

17
evasion or re-labelling than official data from the respective central banks. The reserve requirements were imposed on the borrower’s part of the transaction, hence it might be the case that there were less incentives for lenders to incorrectly report the nature of the capital account transaction with the objective of evading the controls. In addition, as far as Colombia is concerned, the official statistics on capital flows from the _Balanza Cambiaria_ do not discriminate between flows of different maturities. Our data allow for a direct analysis of the effect of capital account regulations on the maturity structure of flows, which has proved to be difficult in the past. In any case, the analysis of a different dataset might prove to be a useful exercise in comparison with the previous literature on the subject. Nonetheless, a major drawback is that the data only encompasses capital flows from and to the United States.

The paper is divided into 5 sections. In the second section we discuss the macroeconomic environment that prevailed in Chile and Colombia during the 1990s and the capital account policies adopted. Subsequently, in section 3, we briefly survey the previous literature on the Chilean and Colombian capital controls. In the fourth section, we present evidence from Generalized Method of Moments (GMM) regressions and Vector Error Correction models (VECM) in order to assess the effects of the price-based capital controls on capital flows and on the real exchange rate. The final section presents the conclusions obtained.

# **2. Capital Controls in Chile and Colombia**

The restoration of democracy in 1990 probably marked the start of the period of greatest prosperity in Chilean history. Chile’s macroeconomic performance and stable environment led the country to be granted an investment grade status by the rating agency Standard & Poor’s in 1992. In fact, it is necessary to place the Chilean price-based capital controls in a wider context. They were an integral part of a macroeconomic policy strategy that allowed Chilean authorities to sustain the crawling band exchange rate regime and target interest rates to stabilize domestic prices, while reducing the excessive pressure that those high interest rates put on the exchange rate.

3
Gregorio Impavido frequency of issues in the primary market, availability and liquidity on the secondary market.

**<u>Table 17: Weighting System for Asset Liability Mismatches</u>**

|**Year of Projection**|**Wk**|
|---|---|
|k <= 5|1|
|5 < k <= 6|0.96|
|6 < k <= 7|0.94|
|7 < k <= 8|0.85|
|8 < k <= 9|0.78|
|9 < k <= 12|0.51|
|12 < k <= 14|0.46|
|14 < k <= 15|0.42|
|15 < k <= 17|0.37|
|17 < k <= 18|0.30|
|18 < k <= 19|0.25|
|19 < k <= 20|0.24|
|20 < k <= 21|0.23|
|21 < k <= 23|0.20|
|23 < k <= 24|0.19|
|24 < k <= 25|0.17|
|25 < k <= 27|0.13|
|27 < k <= 28|0.08|
|28 < k <= 29|0.02|
|29 < k <= 30|0.01|
|k > 30|0.00|

**Source** : CNSF

Table 17 reports the weighting system provided by the CNSF to the industry to weigh eventual mismatches between assets and liabilities in the calculations of the CMG as of March 2006. The weighting system is regularly updated by the CNSF and communicated to the industry when the situation in the financial market requires it. Notice that the weighting system decreases with time reflecting the lack progressive unavailability of longer term instruments.

Ideally, all weight should be equal to one and if this were the case, the CNSF estimates that companies would need to set aside an extra amount of capital equivalent to 25 percent of current technical provisions (or MXN 18,410 million). The methodology used to calculate additional capital requirements in the presence of asset liability mismatches appears to follow a “regulatory maturity gap approach” to asset liability management. It is not clear how this complements or substitutes the economic duration approach that companies need to follow when measuring and monitoring risks. For instance, no reference was found in regulations on the impact that such economic ALM framework based on duration metrics has on capital. Besides, a maturity gap analysis

- 26 -
Table 6: Effects of exposure to COVID-19 using bootstrapped standard errors, rural versus urban

||Wage<br>aspiration<br>(1)|Wage<br>expectation<br>(2)|Aspiration<br>gap<br>(3)|Unrealistic<br>high aspiration<br>(4)|Realistic<br>aspiration<br>(5)|Unrealistic<br>low aspiration<br>(6)|Willing to<br>migrate<br>(7)|
|---|---|---|---|---|---|---|---|
|**Panel A: Rural**||||||||
|COVID shock|-4,868.791|-2,218.601|-2,650.191|-0.312|0.243|0.068|-0.325|
|[|1,692.240]**|[1,591.703]|[690.605]***|[0.082]***|[0.176]|[0.135]|[0.089]***|
||(0.022)**|(0.210)|(0.024)**|(0.007)***|(0.360)|(0.619)|(0.008)***|
|Outcome mean|19,491.57|16,550.58|2,940.99|0.53|0.25|0.22|0.50|
|Observations|1,898|1,898|1,898|1,898|1,898|1,898|1,875|
|**Panel B: Urban**||||||||
|COVID shock|-2,252.945|-890.597|-1,362.348|-0.159|0.034|0.125|-0.022|
||[2,368.673]|[1,679.992]|[2,504.449]|[0.173]|[0.197]|[0.207]|[0.198]|
||(0.608)|(0.581)|(0.682)|(0.408)|(0.844)|(0.777)|(0.917)|
|Outcome mean|20,109.20|17,679.41|2,429.80|0.50|0.26|0.25|0.45|
|Observations|1,282|1,282|1,282|1,282|1,282|1,282|1,268|

_Notes:_ Rural and urban refer to a respondent’s home location. All columns include the full set of controls mentioned in specification (1). Robust standard errors clustered by ITI district are in brackets and p-values from wild-cluster bootstrapped standard errors are in parentheses. Variable definitions are in the online Appendix.<sup>_∗_</sup> _p <_ 0 _._ 1,<sup>_∗∗_</sup> _p <_ 0 _._ 05,<sup>_∗∗∗_</sup> _p <_ 0 _._ 01.

# **References**

- **Abraham, Rosa, Amit Basole, and Surbhi Kesar.** 2022. “Down and out? The gendered impact of the Covid-19 pandemic on India’s labour market.” _Economia Politica_ , 1–28.

- **Allard, Jenna, Maulik Jagnani, Yusuf Neggers, Rohini Pande, Simone Schaner, and Charity Troyer Moore.** 2022. “Indian female migrants face greater barriers to postCovid recovery than males: Evidence from a panel study.” _EClinicalMedicine_ , 53.

- **Arora, Varun, Sujoy Chakravarty, Hansika Kapoor, Shagata Mukherjee, Shubhabrata Roy, and Anirudh Tagat.** 2023. “No going back: COVID-19 disease threat perception and male migrants’ willingness to return to work in India.” _Journal of Economic Behavior & Organization_ , 209: 533–546.

- **Bandiera, Oriana, R Burgess, I Rasul, M Sulaiman, and A Vitali.** 2020. “Worker heterogeneity and job search: Evidence from a six-year experiment in Uganda.” _PEDL Research Paper_ .

10
products as an agent of other _takaful_ operators. The scale of operation of these services is large, but they have not been successful in reaching the poor (Ahmed 2013).

Takaful T&T Friendly Society (TTTFS) is a nonprofit, multipurpose cooperative in Trinidad and Tobago that provides micro _takaful_ services directly to the poor. TTTFS has sustained moderate surpluses over the years that have consistently resulted in an increase in reserves and the distribution of rebates. While the scheme provides _takaful_ services to the poorer sections of the population, it covers only a limited number of members. Another example of a nonprofit organization serving the needs of the poor is Peramu Foundation in Indonesia, which provides micro _takaful_ to its microfinance clients and non-clients. Using the indirect approach, it sells the microtakaful services to the poorer sections of population as an agent of other established _takaful_ operators (Ahmed 2013).

# _Social Sector_

_Zakat_ and _waqf_ can be used to reduce the vulnerability and enhance the resilience of the poor. While traditionally _zakat_ and _waqf_ have acted as safety nets, their application can be expanded to protect the non-poor who are vulnerable to becoming poor due to adverse shocks. One approach is to provide interest free loans (qard hassan) to the vulnerable. Kahf (2004) indicates that in Sudan, _Diwan al Zakat_ has initiated lending to farmers at the beginning of the agricultural season to enable them to buy necessary inputs; the loans are repaid after the harvest. This policy has increased the productivity of farms and increased _zakat_ collection from farmers, equivalent to 74.4 percent of the loans. In case of negative shocks, _zakat_ can be used for debt relief of the poor. Another effective way to reduce vulnerability is to use _zakat_ and _waqf_ funds to pay the monthly _takaful cont_ ribut _ions_ (premiums) to hedge against some defined risks. This scheme can increase the penetration of _takaful_ services among the poor.

# **4. Contribution to Environmental and Social Issues**

Several studie _s_ find that the Islamic financial sector’s role in addressing environmental and social goals is either small or non-existent. In a survey of the social reporting of 19 Islamic banks, Kamla and Rammal (2013) did not find any evidence of Islamic banks contributing to social development or having any ‘serious schemes targeting poverty elimination or enhancing equitable redistribution of wealth in society’ (Kamla and Rammal 2013 _: 933)._ They conclude that the ‘failure to make social justice the core value of their operations has contributed to the failure of Islamic banks to fulfill their ideological claims’ (Kamla and Rammal 2013: 933). Whereas Haniffa and Hudaib (2007) find high scores for commitment of Islamic banks towards stakeholders such as debtors and employees, the commitment towards society scored the lowest.

24
After estimating this ratio for each district, it is straightforward to calculate the percentage change in income levels that can be attributed to climate change.

At the national level, the simulation indicates that past climate change has had a negative effect on overall income levels of about 1%. This modest effect at the aggregate level, however, hides much larger variations at the state and district levels. The jungle state of Loreto, for example, is estimated to have experienced a reduction in incomes of about 5.1%, while the mountain state of Puno is estimated to have benefitted in the order of 5.5%.

**Table 8: Simulated effects of recent climate change on** **<u>income (% change), by region</u>**

|Region|Population<br>2005<br>(thousands|**Total effect of**<br>**recent climate**<br>**change**|
|---|---|---|
|Amazonas|389|-2.4|
|Ancash|1,039|-0.1|
|Apurimac|419|3.4|
|Arequipa|1,141|2.2|
|Ayacucho|619|2.6|
|Cajamarca|1,359|-0.1|
|Callao|811|-3.0|
|Cusco|1,172|3.5|
|Huancavelica|447|3.8|
|Huanuco|731|0.2|
|Ica|666|-1.8|
|Junin|1,092|2.3|
|LaLibertad|1,540|-1.9|
|Lambayeque|1,092|-3.6|
|Lima|7,819|-2.5|
|Loreto|884|-5.1|
|Madre deDios|92|-2.8|
|Moquegua|159|0.7|
|Pasco|267|2.6|
|Piura|1,631|-3.8|
|Puno|1,246|5.5|
|San Martin|670|-3.8|
|Tacna|274|0.2|
|Tumbes|192|-5.2|
|Ucayali|402|-4.8|
|**Total**|**26,152**|**-1.0**|

_Source:_ Authors’ estimations.

Figure 4 plots the estimated change in income at the district level against the income level each district would have had in the absence of recent climate change. The figure indicates 17
X due to a desire to maintain real incomes in the face of declining real producer prices. Thus, assuming that lower prices automatically lead to lower production is putting things too simply. Cromwell and Winpenny also stress the relation between producer prices and input prices: in Malawi maize prices were increased relative to those of other crops in an attempt to improve food security, but the fertilizer removal program resulted in extremely high fertilizer costs for maize, thereby inducing farmers to shift to low-input crops. In addition, when production is stimulated through producer price changes, a simultaneous increase in fertilizer prices may lead to increasing intensity of production by reducing the proportion of land left fallow each year. Their general conclusion is that early reforms seem to have had a negative impact on the environment at the start, particularly on the crop mix and intensity of production, but later reforms appear incidentally to have ameliorated the environmental impact of macro-economic policies.

The link between external debt and the environment has been made the centerpiece of criticism by many enviromnentalists. However, the observation that international debt problems (and the subsequent policy based-lending programs) have accelerated the rate of exploitation of natural resources to enable countries to meet their external financial obligations, has also been challenged. The 1992 _World Development Report_ concludes that the evidence on the debtenvironment observation is limited and contradictory. Reed (1992) argues that the link between government policy makers and a country's natural resources was established long before the debt crisis: in the 1970s govermnents quite often drew on stocks of natural capital to finance ambitious development plans (Reed, 1992: 144). Despite the fact that COte d'Ivoire has the highest deforestation rate in the world, in the Cote d'Ivoire case study, no evidence that debt directly aggravated or eased environmental degradation was established. The Mexican case study did not provide any evidence in support of the debt-environmental thesis, pointing out that response to macroeconomic crisis in the form of increases in natural output requires quite a number of years and often additional capital as well. In the Ihai case study, it was found that the rampant deforestation which occurred during the mid-1980s could not be linked in any direct way to national debt obligations.

# _Resource pncing and resource use_

The 1992 _World Development Report_ emphasized that the cost of energy in developing countries is subsidized - electricity costs on average one third of the cost of supply. The introduction of cost-recovery policies may therefore be expected to lead to greater efficiency in the 109
# **6 References**

Agarwal, B. (2003). “Gender and land rights revisited: exploring new prospects via the state, family and market.” _Journal of Agrarian Change_ , 3.1-2, pp. 84–224.

Allendorf, K. (2007). “Do women’s land rights promote empowerment and child health in Nepal?” _World Development_ , 35.11, pp. 1975–1988.

- Bardasi, E., Beegle, K., Dillon, A., and Serneels, P. (2011). "Do labor statistics depend on how and to whom the questions are asked? Results from a survey experiment in Tanzania." _World Bank Economic Review_ , 25.3, pp. 418–447.

- Beegle, K., Frankenberg, E., and Thomas, D. (2001). "Bargaining power within couples and use of prenatal and delivery care in Indonesia." _Studies in Family Planning_ , 32.2, pp. 130-146.

- CAPRi (CGIAR Systemwide Program on Collective Action and Property Rights). (2010). _Resources, rights, and cooperation: a sourcebook on property rights and collective action for sustainable development_ . Washington, DC: International Food Policy Research Institute (IFPRI).

- Carletto, C., Gourlay, S., Murray, S., and Zezza, A. (2016). “Cheaper, faster, and more than good enough. Is GPS the new gold standard in land area measurement?” World Bank Policy Research Working Paper No. 7759.

- Carletto, C., Gourlay, S., and Winters, P. (2015). “From guesstimates to GPStimates: land area measurement and implications for agricultural analysis.” _Journal of African Economies_ , 24.5, pp. 593-628.

- Chen, J., and Collins, L. (2014). “Let’s talk about the money: spousal communication, expenditures, and farm production. _American Journal of Agricultural Economics_ , 96.5, pp. 1272–1290.

- Dammert, A., and Galdo, J. (2013). “Child labor variation by type of respondent:  Evidence from a Large-Scale Study.” _World Development_ 51, pp. 207-220.

- Deere, C. D., and Doss, C. R. (2006). “The gender asset gap: what do we know and why does it matter?” _Feminist Economics_ , 12.1-2, pp. 1–50.

- Deere, C. D., Alvarado, G. E., and Twyman, J. (2012). “Gender inequality in asset ownership in Latin America: female owners vs household heads.” _Development and Change_ , 43.2, pp. 505–530.

- Deininger, K., Goyal, A., and Nagarajan, H. (2010). “Inheritance law reform and women's access to capital: evidence from India's Hindu succession act.” World Bank Policy Research Working Paper No. 5338.

- Doss, C. (2006). “The effects of intrahousehold property ownership on expenditure patterns in Ghana.” _Journal of African Economies_ , 15.1, pp. 149–180.

- Doss, C., Grown, C., and Deere, C.D. 2008. “Gender and asset ownership:  a guide to collecting individual level data.” World Bank Policy Research Working Paper No. 4704.

29
# Table 5: **Are Star Firms Persistent Performers?**

This table reports estimates from the following panel regression model: Performance is Sales growth/Employment growth (each defined as the 5-year log difference in sales or employment respectively divided by 5), Labor Productivity, Tobins Q ( _Q_<sup>_T OT_</sup> ) or _ROIC_<sup>_T OT_</sup> averaged over 5 years. Log(Assets) is the 5-year lagged value of the logarithm of total assets. HHI is 5-year lagged value of Herfindhal Index of market share in each 3-digit NAICS industry. _Markups_<sup>_T OT_</sup> is the 5-year lagged value of Markups based on the estimation in De Loecker and Eeckhout (2017) using operating expenses as a variable input of production and include correction for intangible capital. Market Share is the 5-year lagged value of the ratio of the firm _i_ s sales to total industry _j_ s sales in a particular year. _ROIC_<sup>_T OT_</sup> Star is a dummy variable that takes the value 1 if firm _i_ s 5-year lagged _ROIC_<sup>_T OT_</sup> was above the 90th percentile of _ROIC_<sup>_T OT_</sup> across all firms 5 years back and 0 otherwise. The regressions are 5-year stacked panel regressions: 1990-1995, 1995-2000, 2000-2005, 2005-2010, and 2010-2015 and include industry and year fixed effects with standard errors clustered at the firm level. Detailed variable definitions are in the Appendix. (<sup>_∗∗∗_</sup> ) _,_ (<sup>_∗∗_</sup> ) _,_ (<sup>_∗_</sup> ) denote statistical significance at 1%, 5%, and 10% levels respectively.

||1|2|3|4|5|
|---|---|---|---|---|---|
||5-year average<br>_ROIC_<sup>_TOT_</sup>|5-year<br>change<br>in Log(Sales)|5-year<br>change<br>in Log(Empl)|5-year average<br>Labor Produc-<br>tivity|5-year average<br>Tobin’s _Q_<sup>_TOT_</sup>|
|L5.ROICTOT Star|-2.780***|0.038***|0.003|0.897|0.985***|
||(0.611)|(0.007)|(0.007)|(10.998)|(0.060)|
|L5.ROICTOT|0.633***|-0.000***|0.001***|1.459***|0.003***|
||(0.009)|(0.000)|(0.000)|(0.144)|(0.001)|
|L5.Market share|-1.675|0.030|0.079**|-4.537|0.734**|
||(1.900)|(0.040)|(0.037)|(83.102)|(0.299)|
|L5.MarkupsTOT|9.592***|0.130***|0.087***|41.803**|0.793***|
||(0.546)|(0.009)|(0.007)|(17.092)|(0.058)|
|L5.Log(Assets)|0.733***|-0.006***|-0.009***|28.268***|0.033***|
||(0.067)|(0.001)|(0.001)|(2.157)|(0.007)|
|L5.Log(Age)|0.276*|-0.025***|-0.018***|-39.109***|-0.191***|
||(0.144)|(0.002)|(0.002)|(4.735)|(0.015)|
|L5.HHI|-4.985**|-0.011|0.025|202.495***|0.153|
||(2.196)|(0.035)|(0.037)|(60.034)|(0.185)|
|N|16392|10762|10415|16106|16001|
|Adj. R-sq|0.732|0.092|0.088|0.402|0.227|
|Fixed Efects|—|————————|–Industry, Year—|———————–|—|
- 32 -

sometimes to Inland Revenue, which administers the income tax, thus splitting responsibility for the various forms of domestic indirect taxes.

The administrative structures and procedures for excises originated with the traditional levies on alcoholic beverages and cigarettes; for these commodities the systems remain largely unchanged in developing countries. As additional commodities were subjected to excises, initially the same procedures were attempted. This proved to be unworkable, and thus simpler techniques have come to be used.

# The Traditional Techniques

Because of the very high rates of the traditional excises, they were particularly subject to evasion, and thus very strict physical control was established, with "physical presence" of the enforcement agency. 14 There are several steps in the process:

1. Licensing. A firm seeking to produce alcoholic beverages or tobacco must register and apply for a license. Detailed information is required about the physical layout of the plant, bonded warehouses, operational procedures, etc. Some countries require annual renewal of the license.

2. Physical Control of Production. Frequently an excise officer is stationed in the plant at all times, or during working hours; in other instances the officer will make regular--often daily--visits to the plant. The officer will check the process of production, the entry of materials, etc., into the plant, and the output, testing the strength as well as the quantity. He will pay particular attention to all transfers of the product from the factory to the bonded warehouse or similar facility, and particularly to the transfer out of the bonded warehouse, the point at which

> 14 In the United Stats, rigid controls were introduced in 1866 after an increase in the tax on distilled spirits caused the revenue to fall in half.