rafmacalaba/datause-encoder-data huggingface dataset:
**Table 3: Exchange Rate Risk Metrics**

|**Before 2007**|**After 2007**|
|---|---|
|Roll-over ratio of foreign currency<br>borrowing|Currency composition of debt stock (local<br>vs. foreign)|
|Currency<br>composition<br>of<br>foreign<br>currency borrowing|Currency composition of FX-debt stock|

# **4. Technical Framework of TDSM**

Based on the conceptual framework described above, the TDSM was built on the Matlab platform interacting with MS Access, Excel, and Word for data input and output. The TDSM operates within three main modules. The first of these modules, ―Debt Stock Database,‖ operates in MS Access, and consists of detailed records of outstanding bond issues. The ―Scenario Generator‖ module produces scenarios for relevant financial variables in the Matlab environment. The ―Cash-Flow Engine‖ module in Matlab subsequently calculates the borrowing requirement based on the payment profile of debt stock, the financial scenarios, and the assumptions about the primary surplus and other cash-flows. The calculated financing need is met using user supplied issuance strategies. The ―Cash-Flow Engine‖ also calculates the overall cost and risk metrics for all strategies iteratively. The following sections elaborate on the technical aspects of TDSM.

# **4.1 Debt Stock Database**

Information on the instruments of the current debt portfolio is held in this database. Each strategy simulation starts with the actual bond portfolio reading from the database, which contains detailed records of the bonds and bills issued by the Treasury in local and international markets.

The configuration of the database reflects the structure of Turkey’s central government gross debt stock that has changed considerably over the last ten years. At the end of 2002, local currency debt represented only about 42% of total debt stock and consisted mainly of shortterm zero coupon instruments, including treasury bills and floating rate notes. The foreign currency-denominated/indexed debt included bonds and bills issued in local markets, Eurobond issuances in international markets, and a substantial external loan portfolio (multilateral agency, bilateral lender, and other creditor debt). In line with the government’s strategic goals, and developments in the Turkish economy, the risk profile of public debt has improved significantly, with increasing maturities in local markets and reduced reliance on 18
**<u>Table 4 Percentage of Goods Traded</u>**

||% Imported<br>Mean<br>Median|% Exported<br>Mean Median|
|---|---|---|
|Export/Import|54<br>50|41<br>30|
|Export Only|‐<br>‐|41<br>30|
|Import Only|56<br>50|‐<br>‐|

# **3.2 Variables of Interest**

The broad scope of the survey allows me to observe a rich set of variables to analyze the underlying factors of firm evolution. The main focus of this study is to analyze the relation between firm evolution and its trade orientation. I use several variables to measure firm evolution. As direct measures of growth, I look at evolution of size measured as employment and sales and evolution of labor productivity. I also analyze different proxies for technological innovation. These measures are product and process innovation, use of quality certificates and foreign licenses. In examining the relation between firm evolution and trade, I control for a rich set of firm characteristics. A complete list of variables used in the analysis is given in Table 5. These variables are likely to affect firm evolution and without controlling for them, it is difficult to identify the exact relation between trade and growth. All data is provided from Enterprise Surveys database.

Data for ECA 2002 and 2005 are given in US dollars but 2006 LAC and 2008 ECA data were in local currencies. Nominal values are deflated using the GDP deflator from the World Bank Development Indicators database. All values are presented in 2000 constant US dollars and the exchange rate is taken from the International Financial Statistics database.

11
severely understate uncorrected standard errors if the outcomes are serially correlated.

# 6.1 Registration

The ...rst prediction of the model above is that the fraction of registered businesses should increase after the reform. Table 5 contains the regressions for the registered business dummy, which denotes the fraction of all people who own a registered business. Both, the speci...cation without controls and the one with individual level and Economic Census controls, show a positive and signi...cant impact of the reform on the number of registered businesses. The increase of 0.32 percentage points is equal to a 3.8 percent increase in registered businesses from the pre-reform level of 8.3 percent.

Columns 3 to 6 of Table 5 show the impact on registered businesses broken down by lowrisk and high-risk businesses. Since only the low-risk businesses are eligible for the reform, the increase in registered businesses should only come from low-risk businesses. This is indeed what the results in Columns 3 to 6 con...rm. The fraction of low-risk registered businesses increased by 0.37 percentage points (a increase of 5 percent from the pre-reform level of 7.4 percent), while there was no statistically signi...cant change in high-risk registered businesses. Based on the fact that the 34 municipalities in my sample had a total population of 8,285,900 between ages 20 and 65, according to the 2000 Demographic Census, an increase of 0.37 percentage points in low-risk registered businesses corresponds to an increase in 30,678 ...rms for all 34 municipalities or 902 ...rms per municipality, on average. The total increase in the number of formal ...rms is 7.6 times bigger than the increase in formal ...rms found in Kaplan, Piedra, and Seira (2006), who estimate only 4,029 new formal ...rms. As explained above, this big di¤erence may be due to the fact that Kaplan, Piedra, and Seira use registration data from the Mexican Social Security Institute (IMSS), which implies that their estimates don’t capture ...rms that have no employees. They do also do not capture ...rms that obtain an operating license but do not register their workers with the IMSS.

The regression above estimates only the average e¤ect of the reform on registration over the post-treatment period. However, it is also important to check how this e¤ect looks over time. Figures 7 shows a plot of the coe¢ cients of the following regression where Quarterl is a set of dummy variables for lag and lead quarters relative to the time of implementation in a given municipality. For example, Quarter�1 is equal to one for the last quarter before the reform was implemented. Since the implementation of the reform was phased in over time and since the data set overs quarters 2000-II to 2004-IV only, I do not observe the 18
24 DASGUPTA AND GROVER Table 3: Port access, highways and economic activity

||∆Output|∆Employment|∆Plant|
|---|---|---|---|
||(1)|(2)|(3)|
|Secondary|0.07|0.08|0.07|
||(0.33)|(0.27)|(0.23)|
|Interior|-0.10|0.03|-0.29|
||(0.50)|(0.40)|(0.32)|
|1994-00_×_Secondary|0.75|0.72<sup>_∗_</sup>|0.67<sup>_∗_</sup>|
||(0.49)|(0.40)|(0.40)|
|1994-00_×_Interior|0.68|0.34|0.65|
||(0.67)|(0.52)|(0.49)|
|2000-09_×_Secondary|-1.06<sup>_∗∗_</sup>|-1.05<sup>_∗∗∗_</sup>|-0.80<sup>_∗∗_</sup>|
||(0.41)|(0.37)|(0.34)|
|2000-09_×_Interior|-1.19<sup>_∗_</sup>|-1.06<sup>_∗∗_</sup>|-0.27|
||(0.61)|(0.49)|(0.49)|
|On GQ|0.15|0.22|0.31|
||(0.28)|(0.25)|(0.23)|
|1994-00_×_On GQ|0.07|0.21|-0.14|
||(0.44)|(0.36)|(0.36)|
|2000-09_×_On GQ|-0.42|-0.64<sup>_∗_</sup>|-0.50<sup>_∗_</sup>|
||(0.35)|(0.34)|(0.30)|
|Secondary_×_On GQ|-0.17|-0.46|-0.47|
||(0.57)|(0.50)|(0.38)|
|Interior_×_On GQ|0.36|-0.20|0.06|
||(0.95)|(0.73)|(0.48)|
|1994-00_×_Secondary_×_On GQ|-0.33|-0.29|0.13|
||(0.75)|(0.67)|(0.56)|
|1994-00_×_Interior_×_On GQ|-1.36|-0.41|-0.05|
||(1.11)|(0.89)|(0.67)|
|2000-09_×_Secondary_×_On GQ|0.85|1.34<sup>_∗∗_</sup>|1.01<sup>_∗∗_</sup>|
||(0.70)|(0.62)|(0.50)|
|2000-09_×_Interior_×_On GQ|1.12|1.38|0.47|
||(1.05)|(0.91)|(0.69)|

The dependent variable is cumulative growth rate of output, employment and plants at the district level. “On GQ” is an indicator variable that takes a value of 1 if a district lies within 10 km of GQ. The omitted category is the primary region not on GQ during 1989-94.<sup>_∗_</sup> ,<sup>_∗∗_</sup> and<sup>_∗∗∗_</sup> correspond to significance level at 10, 5 and 1 percent respectively. Nodal districts are included. All regressions include state-period fixed effects. Standard errors are clustered at the district-level.

tion within secondary region. Grouping “On GQ” districts into two categories: those that were “treated” early (before March 2003) and those that were treated later (Ghani et al., 2016), we
- 53 -

13. West African literature refers often to earrings as wealth. See, for instance, Camara Laye's autobiographical Dark Child, in which the father is a goldsmith, and Sembene Oumane's novelette and film, The Money Order, in which they are pawned to a usurious Mauritanian merchant in Dakar as a desperation measure, and lost.

14. Only one such transaction was reported in interviews.

15. In a preliminary count of data from the two villages studied in Western Division, women who grew groundnuts harvested an average of 732 as much as 'men who grew them. On average, the men sold 73Z of their crop, stored 202 as seed, and stored 32 as food. The women sold 652 of theii crop, stored 132 as seed, and stored 232 as food. While only 272 of the men who grew groundnuts kept any after harvest for use as food, 92 percent of the women groundnut growers kept some for food. All the men growers and 912 of the women growers kept some for seed. Of course, some groundnuts originally intended as seed get consumed before planting time.

16. Because the volume of a storehouse increases faister than the surface as its size increases, by simple geometric principle, there is an economic advantage in larger storehouses. But, as seen later, there are social disadvantages in stores for more than one village.

17. Survey response percentages in this paper refer to the 1988 survey unless otherwise indicated. Figures given are "valid percentages", i.e., they refer to totals excluding "no answer' or "unintelligible" responses and responses discovered in cross-checks to be inaccurate. Figures are rounded to the nearest percentage point.

18. Saving by burial has long occurred elsewhere in Africa. The late President Jomo Kenyatta of Kenya once reported on the Kikuyu, 'they say it is better to buy a sheep or goat instead of shillings which, if buried in the ground (the only form of saving money the majority of the people know), would rot and lose their value" (1965 [1938]: 66).

19. This is not, of course, to say all Gambian marriages are suspicious or hostile. They vary as anywhere. But ties between spouses often seem more distant than some "blood" kin ties, and cash is more likely than other commodities to be privately stashed. As discussed below, spouses sometimes do specifically entrust money to each other for safe keeping. See Field 1940, Moock 1986, and Shipton 1989 for other discussions of the separation of resources between spouses elsewhere in Africa south of the Sahara.

20. For comparisons frora Senegal and Niger, respectively, see Tuck 1983: 66; Graham et al.1987: Ch. IV, 18-21.

21. The difference between the figures is more than men's superior access to banks as alternatives might account for. It suggests that men have greater confidence in their own saving means, perhaps, or that women are more readily accepted as depositors.
of total health expenditures, our results on the impact of recall periods on health expenditures remain tenuous.<sup>6</sup> The combination of large impacts on reported morbidity, doctor visits and whether a day was lost due to sickness together with smaller impacts on health expenditures suggests that much of what was underreported in the monthly surveys were less ―severe‖ illnesses that required smaller expenditures on the part of the household. Therefore, whether monthly or weekly reports should be the ―gold standard‖ for health surveys depends on the underlying question. If researchers are interested in the ability of households to smooth consumption after a major health shock, monthly (or even annual) reports may be sufficient—our data do not suggest that these episodes are easily forgotten. But if researchers want to look at the process through which sickness evolves from something ―minor‖ to something ―severe‖, monthly reporting may erase a significant fraction of the relevant action. Similarly, little is known about the industrial organization of markets for medical care in low-income countries. Since a large fraction of visits to doctors are for selflimiting minor problems—a fraction often guessed to be 80 percent—the degree of underreporting we find could substantially alter the formulation and tests of hypotheses related to these markets.

The remainder of our paper is organized as follows. Section I describes the data. Section II presents the evidence of the overall recall effect independent of its interaction with income. Section III explores the data further in order to illustrate the differentials across income groups and the robustness of our findings to age, education and respondent effects. The last section concludes with a brief discussion of the implications from these findings.

# **Section I: Data**

This paper uses data from two sources. The first is a long-standing panel study of health seeking behavior carried out by the Institute for Socio-Economic Research on Democracy and Development (ISERDD) in Delhi. The study followed 1621 individuals in 300 households from 7 different neighborhoods in Delhi between 2000 and 2002. The localities were chosen through initial contacts developed by the anthropologists on the team. Following these initial contacts, which were used for ―entry‖ into the locality, households within each locality were chosen randomly. In each locality, a street was chosen at random and every fourth household located on the street was asked to participate in the survey. A total of 40-45 households were approached to be part of the survey in each locality, and refusal rates were less than 4 percent in all localities. Considerable time was spent explaining to each household the purpose of the survey and care was taken to

> 6 Until recently, medical insurance for catastrophic events was limited to a small fraction of the population. Some estimates suggest that 10 percent of the urban population has access to health insurance; most of these are richer households or government employees. India recently launched a health insurance program for the poor, which is in its 3<sup>rd</sup> year in Delhi.

4
# 1 Introduction

Recent research on ...rm-level exporting suggests that the idiosyncratic interplay between ...rms and markets plays an important role in shaping trade patterns. Examining detailed data on the exports of French ...rms, Eaton et al. (2011) show that while a multipledestination Melitz (2003)-type model does a good job at explaining several empirical regularities, it fails to come to terms with some important features of the data: (1) ...rms do not enter markets according to an exact hierarchy; and (2) their sales where they do enter deviate from the exact correlations that the basic model would insist upon.<sup>1</sup> To account for these facts, they introduce market and ...rm-speci...c heterogeneity in entry costs and demand. But while the modi...ed framework is more consistent with observed trade patterns, there is still little evidence on how speci...c potential sources of such heterogeneity in entry costs and demand a¤ect the export performance of individual producers.

In this paper, we match historically-determined emigration stocks with detailed ...rmlevel data from Portugal to examine the e¤ect of migrant networks on export participation and intensity across markets and ...rms. Portugal o¤ers unique features for this investigation. First, the motives and timing of the sizable emigration ‡ows observed in the country during the Estado Novo authoritarian regime, along with their steep fall in the aftermath of the democratic revolution of 1974, mitigate the concern that emigration stocks might be endogenous to current trading relationships.<sup>2</sup> Second, emigration ‡ows came predominantly from the Northern region of Portugal, suggesting that ...rms located there are more likely to have close ties with the emigrants. These historical features allow us to investigate not only whether migrant networks matter for export outcomes, but also if they constitute an important source of market and ...rm-speci...c heterogeneity in entry costs and demand.

While accounting for the e¤ect of ...rm productivity heterogeneity and the customary gravity-type regressors, we ...nd that larger stocks of emigrants in a given destination increase the likelihood of export participation. This e¤ect is signi...cantly more pronounced among ...rms that are more likely to have close ties with the emigrants –that is, among producers currently located in North of Portugal; and among ...rms that were already born when the bulk of emigration ‡ows took place. Conditional on a ...rm serving a market, the presence of emigration stocks appears to be an important driver of how much it sells there: using two alternative methods to account for self-selection into export markets – a Tobit model and a Heckman selection model – we ...nd that export revenues tend to increase systematically with the number of emigrants in the destination. Taken together, these ...ndings suggest that migrant networks are an important source of market and ...rm-

> 1 See also Lawless (2009), who provides related evidence for Ireland.

> 2 In particular, the circumstances in which emigration ‡ows took place alleviate concerns of reverse causality.

2
lockdown on the three household asset ownership measures are presented in Panel B. The number of different asset types owned by households decreased slightly by 0.4 asset counts, on average, after the Covid-19 lockdown policy. The negative impact lingers but becomes even weaker for the months that elapsed after the Covid-19 lockdown policy _._ In a similar line, the total number of assets owned by a household also declined slightly, with the loss being equivalent to a decline in number by 0.5. The impact on the number of assets lingers within the first three months, with no substantial evidence of recovery after three months. The last three columns of Panel B, in Table 3, represent the Covid-19 impact on the monetary value of total assets for a household, and there was a 16.7% reduction on average, _ceteris paribus._ In addition, for each month after the Covid19 lockdown, there was a 6.9% reduction in the value of total assets, which translates to a loss of approximately 37,696.5 Comorian francs using the pre- Covid-19 sample mean value. There is no evidence of recovery as the months elapsed after the Covid-19 lockdown policy implementation for the monetary value of asset ownership.

**<u>Table 4: Probit Regression Analysis Results (Poverty Status) (Marginal Effects)</u>**

||**Objective Poverty**|**I live well**<br>|**Subjective Poverty Outcomes**<br>**I live in difficulty**|<br>**I am rich**|
|---|---|---|---|---|
|**Post-Covid**|0.081***|-0.047***|0.017***|-0.048***|
||(0.007)|(0.006)|(0.006)|(0.009)|
|**Observations**|28,902|28,005|28,005|27,131|

**Note:** Robust standard errors in parentheses Estimation by Probit. Marginal effect at means reported Statistical significance: *** p < 0.01, ** p < 0.05, * p < 0.1

Table 4 represents the result of the Probit regression of household poverty status for both objective and subjective measures. An evaluation of the objective poverty indicator, measured by households below the poverty line, revealed an 8.1 percentage point increase, on average, postCovid-19 lockdown. Regarding the subjective poverty measures, the results revealed a 4.7 and 4.8 percentage points reduction for households that self-assessed as living well and as socioeconomically rich, respectively. In addition, the estimation showed an increase of 1.7 percentage points for households that self-assessed as living in difficulties. The overall impact 26
- J ̈antti, Markus, T ̈orm ̈alehto, Veli-Matti and Marlier, Eric (2013). _The Use of Registers in the Context of EU-SILC: Challenges and Opportunities_ . European Union.

- Kim, Nak Nyeon and Kim, Jongil (2013). Sodok jipyo ui jaegumto [reexamining income distribution indices of korea] (in korean). _Journal of Korean Economic Analysis_ , **19,** number 2, 1–57.

- Korinek, Anton, Mistiaen, Johan A. and Ravallion, Martin (2006). Survey nonresponse and the distribution of income. _The Journal of Economic Inequality_ , **4,** number 1, 33–55.

- Lakner, Christoph and Milanovic, Branko (2015). Global income distribution: From the fall of the berlin wall to the great recession. _World Bank Economic Review_ ; Advance Access published August 12, 2015.

- Larsen, Erling (2014). The Engel curve of owner-occupied housing consumption. _Journal of Applied Economics_ , **17,** number 2, 325–352.

- Morelli, Salvatore, Smeeding, Timothy and Thompson, Jeffrey (2015). Post1970 trends in within-country inequality and poverty: rich and middle-income countries. In _Handbook of Income Distribution_ (eds Anthony B. Atkinson and Franois Bourguignon), volume 2A. Elsevier.

- Sz ́ekely, Miguel and Hilgert, Marianne (1999). What’s behind the inequality we measure: An investigation using latin american data. _Research Department Working Paper Inter-American Development Bank_ .

- van Veelen, Matthijs (2002). An impossibility theorem concerning multilateral international comparison of volumes. _Econometrica_ , **70,** number 1, 369–375.

- van Veelen, Matthijs and van der Weide, Roy (2008). A note on different approaches to index number theory. _American Economic Review_ , **98,** number 4, 1722–1730.

- Verme, P., Milanovic, B., Al-Shawarby, S., Tawila, S. El, Gadallah, M. and A.ElMajeed, E. A. (2014). _Inside Inequality in the Arab Republic of Egypt: Facts and Perceptions across People, Time, and Space_ . World Bank.

- World Bank (2014). _Taking stock: an update on Vietnam’s recent economic development_ . World Bank.

27
O.A.M.D.G.

**Brück T (2001):** “Determinants of Rural Poverty in Post-War Mozambique: Evidence from a household survey and implications for government and donor policy”, _Working paper Nr. 67, QEH Working paper series_ , DIW Berlin, German Institute for Economic Research

**Brück T (1997):** “Macroeconomic effects of the war in Mozambique”, _Working paper Nr. 11, QEH Working paper series_ , German Institute for Economic Research, DIW Berlin

**Bütler M (1997)** : “Life-cycle Decision Making and Public Pension Reforms”, _Dissertation Nr. 1974, Universität St. Gallen, Difo-Druck GmbH,_ Bamberg

**Cardenas M, Escobar A (1997):** “Determinants of Saving in Colombia 1925-1994”, _Working Paper R-310_ , Office of the Chief Economist, IADB, Washington DC

**Cohen J, Tita G (1999):** “Diffusion in homicide: exploring general method for detecting spatial diffusion processes” in _Journal of Quantitative Criminology, Vol 15 No 4_

**Collier P, Hoeffler A (1998)** : “On Economic Causes of Civil Wars”, _Oxford Economic Papers 50_ , 563-573

**Collier P, Hoeffler A (2002): “** Greed and Grievance in Civil War.” _Working Paper, Centre for the Study of African Economies,_ University of Oxford

**Cotte A (2001)** : “The effects of socio-economic instability on the Colombian productivity: 1952-2000”, Universidad de Los Andes, Bogotá

**Cuéllar de Martínez, M (1997)** : “Valores y Capital Social en Colombia”, Corporación Porvenir and Universidad Externado de Colombia, Bogotá

**Davenport C, Moore W, Poe S (2003):** “Sometimes You just Have to leave: Domestic Threats and Forced Migration, 1964-1989”, _International Interactions_ 29: 27-55

**Davidson R, Mackinnon J (1993)** : “Estimation and Inference in Econometrics”, _Oxford University Press_

**Demsetz H (1967)** : “Towards a Theory of Property Rights”, American Economic Review Papers and Proceedings 57, 347-59