rafmacalaba/datause-encoder-data huggingface dataset:
some caution. Furthermore, the two digit level does not seem to be most appropriate to draw conclusions about the quality level of products.

The domestic shipment data on the four digit level (SCTG) can be exploited to make a more detailed comparison with international trade flows. Several four digit SCTG product groups in manufacturing goods have an exact counterpart in the HS 1996 classification. However, not all of the HS 1996 product groups that correspond to the HS 1996 classification are recorded in tons as trade quantity. Furthermore, for the reason explained above, the US needs to be by far a net exporter in order to obtain valuable results.

**Table 2:** **_Unit Value Comparison of Domestic and Foreign Shipments_**

|||Domest.|Shipm.|Foreign|Shipm.|**U.V.**|
|---|---|---|---|---|---|---|
|SCTG|Commodity description|Value|Av. U.V.|Value|Av. U.V.|**Diff. %**|
|33|Articles of base metal|234,571|2.01|12,093|3.03|<br>**+50.53**|
|34|Machinery|484,152|7.64|56,562|11.59|<br>**+51.72**|
|35|Electronic & other elec. Equip. & comp. & office equip.|890,803|17.96|149,163|38.93|**+116.70**|
|36|Motorized & other vehicles (including parts)|748,550|5.62|68,768|5.58|<br>**-0.78**|
|37|Transportation equipment, n.e.c.|155,013|8.45|28,238|51.06|**+504.54**|
|38|Precision instruments & apparatus|225,070|12.26|39,314|104.84|**+754.83**|
|39|Furniture, mattresses & mattr. Supp., lamps, light. fittings|139,727|4.29|2,736|5.69|<br>**+32.49**|
|40|Miscellaneous manufactured products|387,426|4.89|24,009|8.88|<br>**+81.60**|
|41|Waste and scrap|37,896|0.17|5,170|0.46|**+165.58**|

Notes: Value stands for the total value of the shipment in current U.S. dollars. U.V. denotes the average unit value of the shipment in each SCTG commodity group. Diff. % expresses the difference in percentage between domestic and foreign shipments All these criteria are only fulfilled by two headings, namely HS 8301 (Padlocks, locks, claps with locks, and keys) and HS 8803 (Parts of aircraft, spacecraft, etc.). For the year 2002, in case of HS 8301, the US exported goods worth 337 million US dollars and imported only half of this amount; and for HS 8803 the exports amounted to 8,584 million US dollars compared to imports of only 197 million US dollars.

Since we are interested in quality trade between similar economies, we have extracted the US export data for both product groups towards the 15 EU countries, plus Canada and Japan, from the UN COMTRADE Database. Table 3 lists in the first two columns of each product group the unit values of exports and the difference in percentage compared to the unit values of domestic shipments. The average unit values of domestic shipments for HS 8301 are 6.71 (US dollars per ton) and for HS 8803 180.72 (US dollars per ton) according to SCTG data.

23
Sanchez-Robles (1998) and Calderón and Servén (2004, 2010a,b) find that these summary measures are positively and robustly related to per capita GDP growth in panel data sets combining industrial and developing countries. The magnitude of the effects is substantial: a 1- percent increase in physical infrastructure stocks, given other variables, temporarily raises GDP growth by as much as 1-2 percentage points, although the growth acceleration gradually tapers off as the economy approaches its long-run per capita income.

The literature cited so far takes a country-level perspective. However, there are also studies that examine the effects of infrastructure development for income growth at a more disaggregated level. For example, Rud (2012) investigates the impact of electricity provision on manufacturing output across Indian states. Electricity provision is not exogenously assigned, and to deal with this problem the study takes advantage of the introduction of a new irrigation-intensive agricultural technology, viewed as a natural experiment. Adoption of new varieties of high-yield seeds required, among other things, timely irrigation, for which electric pumps were used. Thus, the initial availability of groundwater across states is employed to control for the endogeneity of the expansion of the electricity network. The evidence shows that, on average, a one-standard deviation increase in the measure of electrification is associated with a 14 percent expansion in state manufacturing output.

In turn, Datta (2012) examines the consequences of a major road improvement program in India -- the Golden Quadrilateral Program (GQP) -- for the performance of firms. The location of each individual firm relative to the upgraded highway provides firm-specific exogenous variation in the degree to which the quality of the roads improved as a result of the GQP. The study finds that firms located on the highways targeted by the program improved significantly their inventory management and reduced their input costs by switching suppliers.

The bulk of the empirical literature summarized here focuses on measuring the output (or productivity) gains from infrastructure assets. Less attention has been paid to the cost of acquiring and operating these assets. Yet comparison of (social) marginal costs and benefits is necessary to determine whether infrastructure is under- or over-provided.<sup>6</sup>

> 6 To some extent, the reduced-form growth regressions mentioned in the text shed light on this issue, given that their estimates of the impact of infrastructure allow for the adjustment of other production inputs as well as the changes in fiscal parameters required to accommodate infrastructure shocks.

9
**a. Government Revenue**

||Amount in HBS,<br>million TL|Ratio HBS /<br>Administrative data, %|
|---|---|---|
|**Total Revenue (I+II+III)**|**342,692**|**46.4**|
|**I. Tax**|**207,057**|**45.1**|
|**1.Taxes on Income, Profits and Capital Gains**|**69,272**|**49.6**|
|a) Corporate Tax|0|0.0|
|b) Personal Income Tax|69,272|71.7|
|Withholding Tax|65,627|85.2|
|Based on Declaration|3,644|100.0|
|Other|0|0.0|
|**2. Taxes on Property**|**5,259**|**49.6**|
|**3. Taxes on Goods and Services**|**132,526**|**49.4**|
|a) Domestic VAT + VAT on Imports|76,149|58.2|
|b) Special Consumption Tax|52,767|43.8|
|c) Gambling Tax|64|7.2|
|d) Special Communication Tax|3,545|71.2|
|e) Others|0|0.0|
|**4. Other Taxes**|0|0.0|
|**II. Social Contributions**|**135,635**|**73.5**|
|**III. Other Revenue**|0|0.0|

# **b. Government Spending**

||Amount in HBS,<br>million TL|Ratio HBS /<br>Administrative data, %|
|---|---|---|
|**A) Social Spending (I+II+III+IV+V)**|**396,319**|**86.9**|
|**I. Non-contributory Benefits**|**15,507**|**48.4**|
|Old Age Benefit|1,475|93.4|
|Family Benefit|1,133|34.8|
|Disability Benefit|1,518|47.7|
|Home Care Benefit|3,035|60.2|
|Scholarship Benefit|717|30.4|
|Near Cash Benefit|1,288|23.9|
|Health Premium fee waiver|4,957|70.8|
|Widow Transfer for Women|819|101.1|
|Birth Support|565|110.2|
|Others|0|0.0|
|**II. Contributory Benefit**|**160,552**|**78.1**|
|Disability Transfer|1,540|49.2|
|Unemployment Transfers|1,891|50.9|
|Sickness Transfers|882||
|Retirement Pension|126,551|78.9|
|Widow and Orphan pension|29,688|77.2|
|**III. Agricultural Support**|**2,999**|**92.5**|
|**IV. Minimum Subsistence Allowance (AGI)**|**16,632**|**69.7**|
|**V. In-kind transfers**|**200,628**|**100.0**|
|Education|106,616|100.0|
|Health|94,012|100.0|
|**B) Other Spending**|0|0.0|

Source: authors’ calculations.

16
in 1992 were between 40-80% higher than in Poland and the Czech Republic.

The effective marginal tax rate on labor income (at >70%) is high both with respect to other transition economies and to Western European comparators I. Similarly, the effective tax rate on capital income is near the top of the distribution (>80%). The disincentive effects are two fold; affecting labor supply and investment as well as the propensity for tax evasion. In the present context, we can think of the work disincentive primarily in terms of the diversion of effort from the taxed part of the economy to the non-taxed component. We return to this below.

At a more disaggregated level, how have wages behaved ? Until 1992, we observe surprisingly little dispersion in wage changes across branches. But in both 1992 and 1993 it seems that beneath this, there is larger intra-branch wage dispersion. Figures 13-18 give scatters relating the change in wages, deflated by consumer prices, to the change in sales since 1989 at the 3 digit level. Again, a distinction is made over branches with and without sizeable export exposure in 1989 to CMAEA markets. The scatters are quite clear in showing some heterogeneity; branches with high CMEA exposure exhibit a fairly consistent disjuncture in changes to sales and real wages through 1992. And information for 1993 -- which is not strictly comparable -- indicates that this continued into that year. Thus, despite large declines in real sales, wages exhibit surprising real stability and no apparently robust association with changes to sales. The picture that thus emerges is one in which wages appear to be governed by factors exogenous to the branch and branch sales. Branches with above average increases to real sales do not appear to transmit these to wages; inversely, larger than average declines in sales have no significant on wages.

We now explore in some detail wage changes in 1993, using more disaggregated information from the Labor Market Forecast Survey. Table 8 reports our wage estimation. It shows that firm wages were positively and significantly related to sales, investment and bad debts to the firm, as well as to size. Wages were negatively associated with bankruptcy. In terms of firm size, it looks as if small firms have a normal distribution and a reasonably tight wage-revenues association. By contrast, large fims (with >2000 employees) have very 'See EBRD (1993) for the calculations of marginal rates on labor and capital income.

20
Policy Research Working Paper 7480

# **Abstract**

People living in poverty are particularly vulnerable to shocks, including those caused by natural disasters such as floods and droughts. Previous studies in local contexts have shown that poor people are also often overrepresented in hazardprone areas. However, systematic evidence across countries demonstrating this finding is lacking. This paper analyzes at the country level whether poor people are disproportionally exposed to floods and droughts, and how this exposure may change in a future climate. To this end, household survey data with spatial identifiers from 52 countries are combined with present-day and future flood and drought hazard maps. The paper defines and calculates a “poverty exposure bias” and finds support that poor people are often overexposed to droughts and urban floods. For floods, no such signal is found for rural households, suggesting that different mechanisms—such as land scarcity—are more important drivers in urban areas. The poverty exposure bias does not change significantly under future climate scenarios, although the absolute number of people potentially exposed to floods or droughts can increase or decrease significantly, depending on the scenario and the region. The study finds some evidence of regional patterns: in particular, many countries in Africa exhibit a positive poverty exposure bias for floods and droughts. For these hot spots, implementing risk-sensitive land-use and development policies that protect poor people should be a priority.

This paper was commissioned by the World Bank Group’s Climate Change Cross-Cutting Solutions Area and is a background paper for the World Bank Group’s flagship report: “Shock Waves: Managing the Impacts of Climate Change on Poverty.” It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank. org. The authors may be contacted at Hessel.Winsemius@deltares.nl.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Table 5: Gravity Model Regressions for Sub-Saharan Africa: Paired Trading Countries**

Dependent Variable: Log Trade Value ($US)

|Log Exporter GDP|(1)<br>1.563|(2)<br>1.656|(3)<br>1.710|(4)<br>1.706|(5)<br>1.709|
|---|---|---|---|---|---|
||(12.38)**|(13.54)**|(13.92)**|(13.97)**|(14.04)**|
|Log Importer GDP|1.295|1.386|1.434|1.433|1.435|
||(10.26)**|(11.23)**|(11.62)**|(11.64)**|(11.69)**|
|Log Avg. Road Quality|1.984<br>(4.78)**|||||
|Log Min. Road Quality||1.872<br>(7.79)**|2.067<br>(7.99)**|1.991<br>(8.07)**|1.932<br>(8.09)**|
|Log Road Distance|-3.836|-2.531|-2.308|-2.048|-2.096|
||(18.66)**|(9.60)**|(7.46)**|(7.26)**|(7.55)**|
|Trade Agreement Member|||||2.742|
|[WAEMU,CEMAC,EAC]|||||(4.63)**|
|WAEMU|||2.532|2.353||
||||(3.08)**|(3.28)**||
|CEMAC|||2.887|3.400||
||||(2.82)**|(3.41)**||
|EAC|||3.324|3.471||
||||(1.62)|(1.70)||
|ECOWAS|||-0.766<br>(1.18)|||
|SADC|||0.235<br>(0.36)|||
|COMESA|||-1.495<br>(3.02)**|||
|Constant|-32.284|-44.482|-48.982|-51.153|-50.776|
||(7.28)**|(9.44)**|(9.79)**|(10.45)**|(10.44)**|
|Observations|1128|1128|1128|1128|1128|
|R-squared|0.36|0.38|0.39|0.39|0.39|

Absolute value of t statistics in parentheses * significant at 5%; ** significant at 1% Regional Trade Agreements (Country Membership in Appendix Table A7) WAEMU = West African Economic and Monetary Union CEMAC = Economic and Monetary Community of Central Africa EAC = East African Community COMESA = Common Market for Eastern and Southern Africa ECOWAS = Economic Community of West African States SADC = Southern African Development Community 16
country. In contrast, the second and third sets<sup>of indices takean alternative,minimalist approach</sup> as they are based on a single-variable proxy.<sup>The advantage of the compositesetof indicesis its</sup> comprehensiveness while the others' advantage<sup>is</sup> their<sup>simplicity and clarity.Using all of them,</sup> we can examine whether the estimation results<sup>arerobust to changes in returnand risk</sup> measurement. Therefore, their respective results<sup>should be regardedascomplementary.Chart</sup><sup>**I**</sup> summarizes the three alternatives. In all three<sup>cases, co-movementwasmeasured</sup><sup>**by**the</sup> correlation of the relevant return index in a<sup>country and the rest of theworld.'5</sup>

|**Chart1:alternative**|**measuresofreturnandrisk**<br>|
|---|---|
|**Expectedreturn**|**Perceivedrisks**|
|<br>**_1.Co_**|**_mpositeindexb_**<br>|
|Overallproductivity:realpercapita**GDP**<br>th|Generalmacroinstability:standarddeviation<sup>ofreal</sup><br>percapita**GDP**<sup>growth</sup>|
|grow<br>Absenceofpricedistortions:inverseofthe<br>blackmarketPremium**-** i.e.,**_1/(1_**_+bmp)_|<br>Lackofinteational risk-sharing: ratioofexternal<sup>debt</sup><br>todebt +equityexternalliabilities|
|<br>Financialdepth:quasi-liquidliabilities/GDP|Nominalinstability:averageandstandarddeviationof<br>inflation|
|Openness:realimports<sup>plusexports</sup><sup>**/GDP**</sup>|External instability:standard<sup>deviationofreal</sup><br>exchangeratechanges,standard deviationoftermsof<br>tradeshocks,standarddeviationof(imports**+**exports)<br>**/****_GDP_**|
|Institutionalquality:Indicesofgovernance<br>(KaufmnannetaL)and<sup>Gastil civil liberties</sup>|Lowinstitutional quality:negativesofindicesof<br>governance(Kaufmann<sup>et.aL)andGastilcivil liberties</sup>|
|_. <br>Lowtaxburden:negativeofgovernment<br>consumption**/GDP**|<br>Lackoffinancial depth:negativeofquasi-liquid<br>liabilities/GDP|
|<br>Sizeandscaleeconomies:population<sup>size</sup>||
|_2._|_GDP-based_|
|Realpercapita**GDP**growth|Standarddeviationofrealpercapita**GDP**<sup>growth</sup>|
|<br>**_3._**_Sto_|<br>_ckmarket-based_|
|Realstock market return|Standard deviationofrealstockmarketreturn|

Notes: **aAll** standard deviations are computed over the<sup>currentand four preceding years.</sup>

**b** The components listed were aggregated giving<sup>**_50%_**weight to</sup><sup>**GDP**growthin thecaseof return,andits standard</sup> deviation in the case of risk. In **both** cases,<sup>**the**</sup> remaining<sup>componentsreceived equal weights.</sup>

Sources: World Bank World Development Indicators;<sup>IMF InternationalFinancial Statistics;Freedom House;</sup> Kauffmann _et al._ **(1999);** Standard and<sup>Poor's EmergingMarketsDatabase:Shiller</sup><sup>**(1999,**2001).</sup>

> **'** Specifically, we computed rolling correlations<sup>of the return indexina countryand theaverage for the rest of the</sup> world, considering overlapping periods spanning the current<sup>and four preceding years.</sup>

**15**
relatively modest and vary significantly by sector and geographic location, so that for many firms the expected punishment of reverting to informality remains weak.

Several findings emerge. Business formality does not imply labor formality—and vice versa. Despite being registered with SUNAT, 10 percent of the firms in the sample neither have municipal licenses nor register workers with social security. Another 10 percent has workers registered with social security but does not have the municipal licenses to operate. Around 20 percent of the firms have municipal licenses but did not register workers. Finally, only 60 percent of the firms in a given year have the necessary licenses and have registered their workers with social security.

We also observe significant churning in and out of different dimensions of formality within relatively short periods of time. In the span of a year, only two-thirds of the firms maintain their status in the business and labor dimensions. The remaining one-third changes its formality status. Around 10 percent of the firms become more formal, and 20 percent of the firms become less formal. Most firms that change status appear to do so gradually. Very few firms acquire (or lose) business and labor formalization status at once. In most cases, firms choose to become more or less formal along the business or labor dimension, but not along both dimensions at the same time. Such a process supports the view that these firms embark in a gradual process of formalization; evaluate the realized benefits; and choose whether to pursue further formalization, stay partially informal, or even revert to informality in one or both dimensions.

We take advantage of the panel nature of the data to look at firm characteristics that influence year-to-year transitions toward business and labor formality and informality. Businesses with an incorporated legal status (as opposed to unincorporated or natural persons) are more likely to acquire municipal licenses and keep them. In contrast, young firms (less than age four years) are more likely to de-formalize by not renewing municipal licenses. These findings are consistent with the view that young entrepreneurs learn about their productivity in the formal and informal sectors and act upon it. Similarly, firms with greater value added per worker and from regions with larger proportions of firms registering with the Electronic Payroll Registry are more likely to register their workers and keep them registered. These findings suggest that enforcement matters, and—everything else being equal—firms must reach a certain level of productivity before they have the necessary potential to formalize their labor force.

Next, we attempt to infer the extent to which business formalization affects labor formalization and vice versa. Are firms that initiated the process of formalization more likely to conclude it?

4
# the taxes, no matter shared or fixed, were determined by the central government.

Although the 1980-1984 fiscal relation initiated some localities<sup>t</sup> enthusiasm in collecting revenues, the uniform sharing formula created an undesirable surplus in wealthy provinces and deficit in poor provinces. In 1985, the State Council redesigned revenue-sharing arrangement by setting varying schedules based on localities' budget balance in the previous years. The central government allowed financially weak regions to retain more revenues, while continued to maintain a tight grip over regions, including Shanghai, Beijing, Tianjin, Liaoning, Jiangsu, and Zhejiang, that were the most important revenue sources of the centrl revenue. The revenues from these regions generally grew more slowly than the national average since the high share of remittance adversely dampened the localities' enthusiasm in expanding the tax bases. To mitigate this effect, in 1988, the State Council decided to adopt a new system in which six types of central-provincial revenue-sharing methods, each appLied to a number of provinces, were introduced.! These six types are:

1. Contracted Revenue Increase (adopted by ten localities): based on 1987 revenue figures, localities retain a specific proportion ranging from 28 percent to 80 percent of any revenue that is within a certain percentage growth (ranging from 3.5 percent to 6.5 percent; any revenue in excess of 6.5 percent growth is retained entirely by the localities;

2. Uniform rate of retention (adopted by three localities): a fixed share retained by localities (46.5 percent to 46.5 percent depending on the region); 3. Variable rate of remittance (adopted by three localities): a certain proportion is retained up to a quota, and then a different (usually higher) proportion of revenue is retained in excess of the quota; 4. Increased amount contracted to go the center (adopted by three localities): a specific amount is contracted to go to the center in the initial year; in subsequent years the amount was to increase at a contracted rate from 7 percent to 9 percent); 5. Fixed quota (three localities): a specific amount is contracted to be transferred to the center with no annual adjustment for high growth.

6. Contacd transfers to provinces (15 localities): a specific amount is contracted to be transferred from the center to the localities.<sup>7</sup>

**6** See Agarwala (1992) for details.

7 These methods applied to 28 provinces, municipalities directly under the State Council, autonomous regions, and nine cities with independent planning status. The difference between expenditures and income of Hubei and Sichuan provinces was made up from income that Wuhan and Chongqing cities sent to the provinces.

5