rafmacalaba/datause-encoder-data huggingface dataset:
# PPR Working Paper Series

|Title|Author|Date|Contact|
|---|---|---|---|
|WPS94 The World Bank's Population Lending||||
|<br>and Sector Review|George B. Simmons<br>Rushikesh Maru|September 1988|<br>S. Ainsworth<br>31091|
|WPS95 International<br>Trade and Imperfect<br>Competition: Theory and Application<br>to the Automobile Trade|Junichi Goto|September 1988|<br>J. Epps<br>33710|
|WPS96 The Private Sector and Family Planning<br>in Developing<br>Countries|Maureen A. Lewis<br>Genevieve Kenney|September 1988|<br>S. Ainsworth<br>31091|
|WPS97 Export-Promoting<br>Subsidies and What<br>to Do About Them|Richard H. Snape|September 1988|<br>J. Sweeney<br>31021|
|WPS98 Diversification<br>in Rural Asia|Agriculture and Rural<br>Development Staff|October 1988|S. Barghouti<br>38408|
|WPS99 Trade Policies and the Debt Crisis|Sam Laird<br>Julio Nogues|September 1988|<br>S. Torrijos<br>33709|
|WPS100 Public Infrastructure<br>and Private<br>Sector Profitability<br>and Productivity<br>in Mexico|Anwar Shah|September 1988|A. Bhalla<br>60359|
|WPS11 Measuring the Impact of Minimum Wage<br>Policies on the Economy|Luis A. Riveros<br>Ricardo Paredes|October 1988|R. Luz<br>61762|
|WPS102 Effects of the Multifibre<br>Arrangement<br>(MFA) on Developing<br>Countries:<br>A Survey|Junichi Goto|||
|WPS103 Macro Shocks and Industrial<br>Portfolio<br>Responses: An Econometric Model||||
|for LDCs|James Tybout<br>Taeho Bark|||
|WPS104 Financial Crises in Developing<br>Countries|Manuel Hinds|||
|WPS105 Securing International<br>Market Access|Richard H. Snape|October 1988|J. Sweeney<br>31021|
|WPS106 Energy Issues in the Developing World|Mohan Munasinghe|||

Robert J. Saunders
1983-99. Although the pre-1983 ILO October Inquiry contains data on male and female wages for 12 occupations, the analysis in this study focuses on the 1983-99 data..

The main conclusions of the paper are as follows. First, the occupational gender gap appears to be narrowing with increases in GDP per capita,. Second, there is a significantly narrowing impact of trade and FDI net inflows on the occupational gender gap for low-skill occupations, both in poorer and richer countries, and for high-skill occupations in richer countries. Third, there is no evidence of a narrowing impact of trade and evidence of a widening impact of FDI net inflows on the high-skill occupational gender gap for poorer countries, possibly reflecting skill complementarities. And finally, wage-setting institutions have a strong impact on the occupational gender wage gap in richer countries.

# **2.   Measuring the Occupational Gender Wage Gap Using the ILO October Inquiry**

Since 1924 the ILO has conducted an “October Inquiry” on pay by occupation across the world. The ILO sends a questionnaire to national governments asking for wages in detailed occupations, within particular industries.<sup>3</sup> To assure comparability of occupational definitions across the countries, the ILO specifies in great detail the work involved in each occupation. To get a flavor of the specificity consider the following description of a clicker cutter in the footwear industry: _Clicker cutter (machine). Operates press machine which cuts out upper parts of footwear; lays material on the table of machine; selects cutting dies; arranges dies on material to cut it economically and avoid weaknesses; cuts out show part by lowering press onto dies; removes cut-out parts from material._ Or this (abbreviated) description of an accountant in a bank: _Accountant. Plans and administers accounting services and examines, analyses, interprets and evaluates accounting records for the purpose of giving advice on accountancy problems or preparing statements and installing or advising on systems of recording costs or other financial and budgetary data: ... keeps record of all taxes, fees,_

> 3 Some occupations occur in multiple industries (such as ‘labourer’) and in that case the ILO has collected wage data for these occupations in _each_ of the industries.

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# _Household consumption and saving heterogeneity_

In a model that fully integrates household production and consumption decisions, consumption expenditure is given by the household’s spending on _full_ consumption, defined to include market goods and domestic output. A standard assumption in the estimation of commodity demand systems is that consumption and leisure are separable. However, since the systems are typically estimated on household survey data for market consumption spending only, the assumption implies that market goods and non-market time are separable. This means that empirical work on the estimation of commodity demands systems assumes that the output of household production does not have close market substitutes. This is clearly implausible for developed economies, particularly in the case of families with young children. Thus, the parameter estimates can be expected to be subject to bias due to omitted domestic price variables and an incorrectly measured household consumption variable.

The practice of estimating demand systems on data for spending on market goods only is also problematic for modeling life cycle consumption and saving behavior. The core of the life cycle model of consumption choice is the hypothesis that the household chooses its consumption at any point in time in the light of its entire lifetime income stream, using the capital market to decouple current consumption from current income, so as to keep its discounted marginal utility of consumption constant over time.<sup>37</sup> In empirical work, the consumption variable is again expenditure on market goods and services, and the income stream that appears (usually exogenously) in the model is market wage income. In the developed economies’ literature, when predicted consumption and saving paths are compared to the data, not surprisingly there are striking differences. These are presented as “puzzles” in need of solving. However, the differences can be explained by the life cycle profile of female labor supply, and the substitution of domestic for market output that it reflects, after the arrival of children,<sup>38</sup> together with the constraints of an imperfect capital market. Time use data show a large drop in pure leisure, particularly for the mother, after the arrival of children, which suggests that parents reduce their leisure to

> 37 For a comprehensive survey of the theory and evidence see Deaton (1992). 38 See Apps and Rees (2001)

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# **4 Conclusions**

In this paper, we addressed the following three research questions: (i) Are there significant differences in export participation and performance and in the perceived investment climate for exporting in core versus non-core regions? (ii) What is the effect of regional determinants, including the investment climate and agglomeration economies on exporting behavior? (iii) Do the determinants of exporting have a differential effect if firms are located in core versus non-core regions? We used a cross-section covering more than 40,000 manufacturing and services firms in 79 developing countries.

We find that the average share of exporting firms is higher in core regions for manufacturing firms, while there is no significant difference in export intensity. This finding is important as it suggests that the difference lies in export participation, but once the threshold of export participation is reached, there is no difference in the experiences of firms in core versus non-core regions. In services, export participation, on the other hand, does not show a significant difference between core versus non-core regions. Contrary to the findings in manufacturing, this implies that the threshold of export participation might be lower, but differences in export intensity are more difficult to achieve in non-core regions.

Our econometric findings affirm the importance of firm-specific characteristics in determining export performance. But they also highlight the role of locational factors, including the investment climate, but most importantly the role of agglomeration.

Regarding regional determinants of exporting, our overall results for manufacturing firms show that only customs and electricity are determinants of export participation, while all regional determinants are significant in the core and mostly show the expected signs. The regional determinants for services firms are somewhat ambiguous. While the signs are mostly as expected in the overall sample and in non-core regions, almost none of these effects is significant, suggesting that regional determinants are less important for services firms. In core regions, only credit and corruption show the expected coefficient signs.

We also included three measures on agglomeration economies, namely urbanization and localization economies and export spillovers. Urbanization economies appear to reduce the likelihood of exporting, across virtually all firm sizes and locations, whereas export spillovers 27
and ending date of eligibility. This data set was provided separately and was merged with unemployment spell records by personal identifiers and date of registration at the employment office. The accuracy of information on exits from unemployment -- a particular problem for the administrative data obtained from employment offices -- is ensured by a requirement that, when they find a job, unemployed workers have to retrieve the "work booklet" from employment offices and bring it to their new employer, thus signaling employment offices information on exit. Moreover, the coverage of the data is reasonably good since unemployed workers in Slovenia have had strong incentives to register at employment offices.<sup>6</sup> According to the Slovenian labor force survey, in 1989 and 1990, 77 percent of those unemployed according to the International Labor Organiation (ILO) definition were also registered with employment offices, and in 1991 this proportion increased to 83 percent. Missing from the registers are probably school-leavers early in their job hunt.

Two features of the data recorded in the unemployment register should be noted. First, exits from unemploymen **t** o employment include only exits to formal jobs, though these may be jobs either within the social or private sector. Exits for persons who find work under "contract employment" (see above) or in the gray economy are not recorded. For example, according to the Slovenian labor force survey, 42 percent of registered unemployed were performing paid work of at least one hour in the reference week in 1990. Second, the 1992 data on unemployment spells for young persons are not entirely comparable to those for earlier years. In cases where a young person registers as unemployed, leaves unemploymen **t** o take a fixed-term internship, and then re-registers as unemployed, the second unemployment registration date is overwritten on that individual's original 6 For those who have lost a job, incentives are the most powerful, since even a previous nine-month employment makes them eligible for unemployment compensation (see above). Other incentives includ **e** mployment office services (counseling, training, employment subsidies); lower likelihood that a spouse will be laid off, since having an unemployed member of the family influence redundancy decisions; ability to enroll in evening postelementary education (only day-time enrollment is permitted otherwise); subsidies for child care; priority in queues for renting or buying apartments; eligibility for child allowances; and eligibility for voluntary old-age insurance.

11
21 course, had to do with the problems involved in computing the premium associated to QRs, as well as with the absence of reliable data on import tariffs.

Researchers have developed two types of strategies to deal with this problem. (a) Some, as the Krueger-Bhagwati study, the World Bank (1987) and Choski et al. (1988), have resorted to the construction of subjective indexes of trade orientation. (b) Another group of researchers have chosen to decompose the question of the effects of trade orientation on economic performance into two stages. The first stage basically amounts to assuming -- without testing rigorously -- that a more liberalized regime will encourage exports via a reduction of the antiexport bias.16 At the second stage, then, the researcher usually tests whether higher exports (or a more rapid growth in exports) have indeed been associated with a higher rate of output growth (Michaely 1977, Balassa 1978, 1982).

Multicountry Studies The Krueger-Bhagwati NBER project dealt with 10 countries -- Brazil, Chile, Colombia, Egypt, Ghana, India, Israel, Philippines, South Korea and Turkey -- during the period 1950-1972. Detailed data on a number of variables, including ERPs and DRCs rere used to classify each country at a particular moment in time in one of -Aie Phases previously defined in the 15The subjectivity of the indexes employed in the Krueger-Bhagwati study is, however, rooted on some objective indicators. In particular, as mentioned below, in the empirical analysis Krueger tries to control for the different degrees of distortions prevailing in each country.

160f course the difficulty in computing B is at the heart of them assuming that this relation between B and exports holds.
27

# **Graph 1**

Stock Market Prices in Reai Terms Argentina, B razil and M exico 1980 -2001 <!-- Start of picture text --> 12-<br>10 Bra z i I<br>8 -<br>6<br>4<br>80 82 84 86 88 90 921 94 96 98 00<br>| = Argentina ----- Brazil --- Mexico|<br><!-- End of picture text -->

<!-- Start of picture text --> StockMarketPrices in RealTerms 1984 -2001<br>6- Chile, Colom bia, Peru<br>5 Colom bia .<br>4 -~~~~~~~~~~~~~<br>2<br>-~~<br>o3<br>1<br>84 86 88 90 92 94 96 98 00<br>| ~Chile ---- Colom bia --- Peru<br><!-- End of picture text -->
|**Ln sales**|**(8)**<br>0.500***<br>[0.155]<br>0.043***<br>[0.016]<br>-0.577<br>[0.377]<br>-0.112<br>[0.154]<br>0.957***<br>[0.139]<br>0.347***<br>[0.128]<br>0.017<br>[0.029]<br>0.052<br>[0.214]<br>-0.133<br>[0.192]<br>-6.928**<br>[3.324]<br>96<br>0.71<br>0.95<br>e basic set of<br>tional|
|---|---|
|**Ln total**<br>**assets**|**(7)**<br>0.454**<br>[0.180]<br>0.049***<br>[0.017]<br>-0.819**<br>[0.416]<br>-0.13<br>[0.158]<br>0.966***<br>[0.148]<br>0.367***<br>[0.118]<br>0.021<br>[0.023]<br>0.039<br>[0.251]<br>-0.486**<br>[0.215]<br>-4.665<br>[3.704]<br>96<br>2.05<br>0.73<br>umns (1) – (6) th<br>nclude two addi|
|**Ln sales**|**(6)**<br>0.489***<br>[0.156]<br>0.045***<br>[0.016]<br>-0.627*<br>[0.378]<br>-0.111<br>[0.155]<br>0.952***<br>[0.138]<br>0.350***<br>[0.125]<br>0.017<br>[0.029]<br>0.056<br>[0.214]<br>-0.122<br>[0.195]<br>-6.473*<br>[3.331]<br>96<br>0.56<br>0.76<br>ls presented in col<br>umns (7) and (8) i<br>regressions.|
|**Ln total**<br>**assets**|**(5)**<br>0.468***<br>[0.180]<br>0.047***<br>[0.017]<br>-0.766*<br>[0.408]<br>-0.13<br>[0.157]<br>0.971***<br>[0.146]<br>0.362***<br>[0.117]<br>0.02<br>[0.024]<br>0.033<br>[0.250]<br>-0.496**<br>[0.212]<br>-5.16<br>[3.648]<br>96<br>1.68<br>0.43<br>at 1%. In mode<br>fications in col<br>r the first stage|
|**Ln sales**|**(4)**<br>0.398**<br>[0.162]<br>-0.084<br>[0.221]<br>-0.092<br>[0.125]<br>0.948***<br>[0.114]<br>0.439***<br>[0.131]<br>0<br>[0.025]<br>0.101<br>[0.186]<br>-0.368**<br>[0.159]<br>-9.262***<br>[1.576]<br>96<br>0.03<br>0.98<br>** significant<br>rt costs). Speci<br>See table 4 fo|
|**Ln total**<br>**assets**|**(3)**<br>0.367**<br>[0.180]<br>-0.18<br>[0.201]<br>-0.11<br>[0.127]<br>0.970***<br>[0.122]<br>0.461***<br>[0.120]<br>0.002<br>[0.019]<br>0.082<br>[0.223]<br>-0.760***<br>[0.179]<br>-8.358***<br>[1.823]<br>96<br>0.26<br>0.88<br>icant at 5%; *<br>ty and passpo<br>men’s travel.|
|**Ln sales**|**(2)**<br>0.311**<br>[0.152]<br>0.086<br>[0.302]<br>-0.084<br>[0.117]<br>0.968***<br>[0.113]<br>0.514***<br>[0.120]<br>-0.003<br>[0.024]<br>0.134<br>[0.188]<br>-0.455***<br>[0.155]<br>-11.578***<br>[2.524]<br>96<br>1.36<br>0.51<br>at 10%; ** signif<br>populations densi<br>restrictions on wo|
|**Ln total**<br>**assets**|**(1)**<br>0.276*<br>[0.166]<br>-0.036<br>[0.279]<br>-0.102<br>[0.124]<br>0.986***<br>[0.121]<br>0.536***<br>[0.109]<br>-0.001<br>[0.018]<br>0.117<br>[0.225]<br>-0.842***<br>[0.179]<br>-10.354***<br>[2.809]<br>96<br>1.61<br>0.45<br>* significant<br>ck in the EU,<br>migration and|
||Ln total migration to US<br>Ln tertiary migration to US<br>Share of tertiary migration to<br>US<br>Ln distance<br>Conflict nineties<br>Ln GDP per capita in US dollars<br>Ln population<br>Inflation average<br>Governance<br>Year dummy<br>Constant<br>Observations<br>Hansen J statistic<br>Chi-sq p-value<br>Robust standard errors in brackets<br>instruments is used (migration sto<br>instruments: legal restrictions on|
**_Quality – perceptions:_** Commercial perception of water service is one of the highest ratings of all groups at 5.7 out of 7, while the rating for upper-middle-income is 5 and SSA is 4.2. Botswana also has higher rating than OECD at 5.2.  Given the level of access level, the high ranking is not a surprising but the fact that it is higher than OECD may reflect a slight “urban bias” of the perception indicator.

34
United States were selected as the industrial countries, and China, Brazil, India, the Republic of Korea, Malaysia, Mexico, South Africa, and Turkey were selected as the developing countries.<sup>2</sup> Most market share analyses have been carried out using only exports, and testing whether the exports of a specific country have expanded at the same rate as world exports (Balassa (1984); Fosu (1990); Ng and Yeats (1997 and 2003); Mayer (2004); Hanson and Robertson (2009) etc). These exercises take the world trade growth as given and estimate the relative performance of counties against this trend, and not what determines that trend. The contribution of market share changes versus demand increases in explaining trade growth has not received much attention.<sup>3</sup> One simple way of analyzing this issue is to see whether the growth of imports in selected markets are driven by the demand increases or they have expanded by gaining market shares in the importing countries. This can be done by estimating the shares of imports in domestic absorption and then measuring the changes in these shares. These changes in shares show the contributions of share changes while import increases under constant market shares show the contribution of demand increases. This decomposition can also shed light on the likely outcomes for world trade growth under different global demand growth scenarios.

A related issue involves the role of developing (especially emerging market) countries in world manufacturing trade. Many have also argued that developing country exports are taking a big share of the markets in industrial countries and that within manufacturing a significant portion of production is moving from industrial to developing countries. Some have even argued that this development is leading to deindustrialization of many industrial countries. Along with the decomposition exercise, this paper also estimates the magnitude of developing country exports (aggregate and 3 digit) within the domestic absorption and production in these selected countries (both industrial and developing) and their evolution over the last two decades.

Finally, the study analyzes two periods with very different trade growth rates. World trade growth in current US dollars accelerated for all countries during 2001/02-2007/08 period but the acceleration of export growth of developing countries was greater and reached 18.2 percent per annum during this period. As a result developing countries have increased their

> 2 It would be desirable to undertake this analysis for aggregate developing and industrial countries but manufacturing production data is not available in the same format and definitions for many countries. Sample countries account for more than 50 percent of world trade (Table 1).

> 3 This decomposition was undertaken for selected industrial countries for the 1990s (World Bank 2005).

3
goods. Freund and Rocha (2011) investigate sub-components of the Doing Business trade cost measures, and find that only inland transit times have significant effects on African countries’ exports. Hornok and Koren (2014) and Persson (2013) link time in trade to different measures of the composition of trade.<sup>5</sup> While these studies are interesting because they quantify the effects of cross-country variability in the administrative hurdles required to trade, their findings are not informative about the impacts of policy reforms in customs procedures as our study is for Albania.

To our knowledge the only study on the link between the use of risk management procedures and trade is Volpe Martincus _et al._ (2014). These authors use Uruguayan export transaction data to link allocation to red channel inspections to border delays, and border delays to reduced rates of export growth using the IV framework that we employ. While our methodology follows theirs, our study differs from theirs in two important ways. First, our estimation sample occurs during a period of substantial reductions in the probability of physical inspection. Such reductions in inspections were due, in large part, to increased capabilities for risk management in Albanian customs resulting from an extended episode of trade policy reforms.<sup>6</sup> Second, we focus on imports rather than exports. Estimates of the impact of inspections on imports may be more useful, since countries are generally more interested in controlling imports than exports, inspections and delays are more common for imports, and hence policy reforms in customs are likely to have more impact on imports than exports.

Our study also builds on work by Hummels and Schaur (2013), who estimate a tariff-equivalent of the costs of time in trade. Those authors exploit freight logistics choices in U.S. imports to estimate firms’ willingness to pay for reduced time in transport. They calculate that a day in transit acts like an ad-valorem tariff-equivalent trade cost ranging from 0.6 percent to 2.1 percent. Relying on outside estimates of a key structural parameter, we are able to use the

> 5 Hornok and Koren (2014) show that countries with higher administrative trade costs (according to the _Doing Business indicators_ ) per shipment import fewer and larger shipments. Persson (2013) shows that higher export transaction costs (measured by time to export) decrease the number of exported products (the extensive margin of trade).

> 6 Because policy changes other than risk management may also have contributed to lower inspections we are not able to attribute the effects solely to risk management reforms. Technically, the policy reform that we evaluate is the reduced rates of physical inspections that occur over our sample, and clearly most of the observed reduction can be linked to the improvement of riskbased mechanisms for selecting shipments for inspection.

4