rafmacalaba/datause-encoder-data huggingface dataset:
As a result, U.S. import competing industries are much more opposed to eliminating zeroing than were EC import competing industries. In turn, their strong opposition to reform makes it difficult for the USDOC to stop zeroing. Said differently, the current U.S. compliance – stopping zeroing in original investigations – is essentially costless. The _de minimis_ dumping margin in original investigation is 0.5%. In other words, if the home market price is $100 and the export price is $99.49 then the case will be allowed to proceed. But, when the administrative review is conducted the exact same transactions would result in a larger dumping margin because of zeroing. Thus, the real economic impact of zeroing – both in terms of the margin imposed and the uncertainty surrounding that margin – is driven by the _review_ stage.

# **6. The Impact of Zeroing on Margins and Duties**

We now turn beyond the theory to the empirical question of the impact of zeroing on AD margins.<sup>29</sup> Getting an accurate measure of the impact of zeroing on margins is difficult. The fundamental problem is that the USDOC uses firm level pricing in both the home and export markets to calculate margins. What we would like to do is compute the counterfactual “what if there were no zeroing” and then compare the counterfactual margin to the actual margin with zeroing. The calculation of this counterfactual requires access to confidential firm-level pricing data and that is something we do not have. We

> 29 An important affect of zeroing is the additional uncertainty created for importers buying from subject suppliers.  We know of no empirical evidence on this latter impact so we will just focus on how zeroing affects the size of the margin.

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<!-- Start of picture text --> Figure 1 Payments of Taxes and Benefits of Public Spending by Fiscal and Care categories (Million JOD)<br>2,000<br>1,500<br>1,000<br>500<br>0<br>-500<br>-1,000<br>No workers, No workers, Pensioners One/two One/two No Single adult, Married Other care<br>no children in worker, no worker, dependents dependents couple, categories<br>dependents school dependents children in dependents<br>school<br>Direct Taxes Indirect Taxes - direct Indirect Taxes - indirect<br>Direct Transfers Total Indirect Subsidies - direct Total Indirect Subsidies - indirect<br>In-kind Spending (education) In-kind Spending (health) Total Impact<br>Total Cash Impact<br>Millions<br>Fiscal Revenue / Expenditure (JD)<br><!-- End of picture text --> <!-- Start of picture text --> Figure 2 Payments of Taxes and Benefits of Public Spending by Household by Fiscal and Care categories (Percentage of Market<br>Income)<br>100<br>80<br>60<br>40<br>20<br>0<br>-20<br>No workers, No workers, Pensioners One/two One/two No Single adult, Married Other care<br>no children in worker, no worker, dependents dependents couple, categories<br>dependents school dependents children in dependents<br>school<br>Direct Taxes Indirect Taxes - direct Indirect Taxes - indirect<br>Direct Transfers Indirect Subsidies - direct Indirect Subsidies - indirect<br>In-kind Spending (education) In-kind Spending (health) Total Impact<br>Total Cash Impact<br>Fiscal Revenue / Expenditure (Percentage of Market Income)<br><!-- End of picture text --> Source: 2017-18 Household Expenditure and Income Survey <u>(HEIS) and World Bank calculations.</u>
# **Contents**

|**1**<br>**Intr**|**oduction**|**1**|
|---|---|---|
|**2**<br>**Sum**|**mary of DR-CAFTA**|**1**|
|**3**<br>**Pre**|**vious Empirical Evaluations of DR-CAFTA**|**2**|
|**4**<br>**Hon**|**duras before DR-CAFTA**|**4**|
|4.1|Social Accounting Matrix<br>. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|4|
|4.2|Labor volumes and labor market segmentation<br>. . . . . . . . . . . . . . . . . . . . .|7|
|4.3|Structure of protection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|8|
|4.4|Structure of production and demand . . . . . . . . . . . . . . . . . . . . . . . . . . .|11|
|**5**<br>**Mo**|**del Description**|**13**|
|**6**<br>**Tra**|**de Reform**|**17**|
|6.1|Description of simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|17|
|6.2|Macroeconomic results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|19|
|6.3|Sectoral results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|22|
|6.4|Factor markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|26|
|6.5|Compatibility of regional liberalization with multilateral reform . . . . . . . . . . . .|28|
|**7**<br>**For**|**eign Direct Investment**|**30**|
|7.1|Description of simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|30|
|7.2|Macroeconomic results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|36|
|7.3|Sectoral results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|38|
|7.4|Factor markets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .|41|
|**8**<br>**Con**|**clusions**|**43**|
|**A CE**|**S aggregation of Armington demand with non-unitary income elasticities**|**47**|
|**B SA**|**M accounts**|**49**|
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# **V. DISCUSSION**

# **_Financial needs for infrastructure development: revisited_**

As mentioned above, an important problem in the previous literature forecasting the infrastructure financial needs is that the unit cost is assumed constant, whatever its basis is. It means that the roles of procurement efficiency and contract design are ignored.<sup>15</sup> However, these cannot be underestimated as shown in the previous section. In reality, for instance, how to design road procurements is crucial to contain government purchasing costs (Grimm, _et al_ ., 2006). The ROCKS database covering more than 3,000 road contracts over the developing world reveals that the majority of road contracts are less than 60 km, which would result in higher unit costs than our efficient procurement price, holding other conditions constant; these contracts were in fact awarded with extremely high unit prices (Figure 18).

Figure 18. Size and Unit Cost of Road Contracts <!-- Start of picture text --> 0 100 200 300 0 1 2 3<br>Length of roads constructed (km) Unit cost of road construction per km (million US$)<br>.4 .4<br>.3 .3<br>.2 .2<br>Fraction Fraction<br>.1 .1<br>0 0<br><!-- End of picture text --> Source: Author’s calculation based on ROCKS database.

Using our estimation results, the financial needs are reassessed with particular focus on procurement efficiency and less attention paid to the quantity side. We concentrate on examining the unit price impact. The quantity of infrastructure demand—thus supply—is projected by the simple cross-country bivariate relationship between economic development

> 15 Fay and Yepes (2003) assumes that the unit cost of electricity infrastructure is $1.9 million per MW; for roads, $0.41 million per km; for water connection, $400 per household; and for sanitation connection, $700 per household.
2

# **1. Introduction**

Since 2000, banking credit to the private sector has declined in real terms and as a share of Egypt’s GDP. During the past decade the banking system witnessed recapitalization of public banks and two different cycles of external capital flows. Capital flowed in until mid-2008 when the global financial crisis erupted, and flowed out until mid-2009. As global risk appetite recovered, capital flowed back in until the last quarter of 2010, when global capital markets tightened again and the January 2011 uprising accentuated the capital outflow.

Aside from the capital flows’ stop-go cycles, public finance deficits and financing needs created an expansion-contraction-expansion cycle that affected bank credit to the private sector. Output fluctuations with episodes of high growth as well as output contractions affected the private sector’s demand for credit. This paper describes how these factors interact to produce a decline in credit to the private sector.

The paper first examines the stylized facts of bank credit to the private sector in an international context, benchmarking the expected amount of private sector credit for a country with Egypt’s characteristics (using FINSTAT, a benchmarking tool developed by the World Bank). It also explores the evolution of banking sector sources and uses, based on its aggregate balance sheet and similar exercises performed for Latin America and the MENA regions (Barajas et al., 2002; 2010).

The central objective of the paper is to estimate credit supply and demand equations in line with the abundant empirical literature on the topic. Some studies examine the issue assuming that prices are flexible enough to clear the market by equalizing supply and demand. Others assume that prices are not perfectly flexible and estimate demand and supply equations using the short-side rule (i.e. that observed credit quantities can occur on the demand or supply schedules, whichever is smallest, at a given interest rate). Assuming an excess supply or demand at a given point, the researcher infers the likelihood of the observed quantity being on the supply or demand regimes. Empirical studies based on aggregate time series data and applied to business loans include Laffont and Garcia (1977) for the Canadian market, Sealey (1979) and King (1986) for the US market. Pazarbasioglu (1997) and Kim (1999) investigate whether there was a credit crunch, respectively in Finland following the banking crisis of 199192, in Korea following the financial crisis in December 1997. In Latin America, Catao (1997) and Braun and Levy-Yeyati (2000) assessed credit contraction for Argentina, Berrospide and Dorich (2001) for Peru, Carrasquilla, Galindo and Vasquez (2000) and Barajas, Lopez and Oliveros (2001) for Colombia, Barajas and Steiner (2002) for Colombia, Peru and Mexico, and Hurlin and Kierzenkowski (2007) for Poland.
**Poc,Planning, and Research Women ht Development**

Do public programs and infrastructure that promote agricultural growth improve real agricultural wages and thus reduce rural poverty?

That depends, says Khlandker, basing his conclusions on district-level panel data from India.

Whether public policies increase real agricultural wages depends on whether they promote rural nonfarm employment, to absorb the growing labor force.

For example, although educational infrastructure, public inigation, and regulation of markets raise agricultural output, they depress real agricultural wages because they do not increase nonfarm employment In contrast, rural electrification, roads, and banks can increase real agricultural wages, because they increase nonfarm employment.

Rural financial institutions and electrification reallocate labor from agriculture to rural nonfarm activities, however, while roads promote both farm and nonfarm employment.

This paper is a product of the Women in Development Division, Population and Human Resources Department. Copies are available free from the World Bank, 1818 H Street NW, Washington DC 20433. Please contact Belinda Smith, room S9-125, extension 35108 (25 pages with tables).

The PPR Working Paper Series disseminaies the findings of work under way in the Bank's Policy, Planning, and Research Complex. An objective of the scries is to get these findings out quickly, even if presentations are less than fully polished. The findings, interpretations, and conclusions in these papers do not necessarily represent official policy of the Bank.

Produced at the PPR Dissemination Center
effects that are due to EU preferences. Finally, we then re-calculate our estimate of EU preference erosion after adjusting for the administrative cost threshold of 4 percent identified in the previous section. This has a substantial impact on the estimated scope for preference erosion.

Our estimates of the dollar impact of full preference erosion on real national income are shown in Table 6. We have included the impact on the LDCs in Sub-Saharan Africa, as well as other low-income countries in our sample (using the World Bank classification of countries by income). The tables reveal that EU preferences are very important, as a bilateral measure, for Sub-Saharan African countries. Given the current trade policy landscape, we estimate EU preferences to be potentially worth some $460 million annually to African LDCs. Asian countries benefit less, with the exception of Bangladesh ($100 million). These are therefore countries that stand to lose—all other things equal—from a move by the EU to lower MFN trade protection. Other developing country groups stand to gain—these are the “less preferred” in the overall hierarchy of preferences.<sup>24</sup> Although we are not convinced that the potential preference rents all actually accrue to the exporting countries (again, see Olarreaga and Özden 2005), our estimates provide a measure of what is at stake.<sup>25</sup> Our welfare estimates cannot be compared directly to the results obtained in recent partial equilibrium-based analyses such as IMF (2003) and Alexandraki and Lankes (2004) as these focus solely on trade effects. The IMF estimates the potential export revenue loss from preference erosion resulting from a 40 percent cut in protection by Canada, the EU, Japan and the US at some $530 million. This assumes full utilization of preferences and that developing countries get all of the associated rents. Alexandraki and Lankes (2004), focusing on middle-income countries only, conclude that potential erosion impacts are less than 2 percent of total exports for the countries that are most “preference dependent”.

Limão and Olarreaga (2005) are to our knowledge the only paper to undertake an analysis of the welfare effects of complete preference erosion. They calculate what the income transfer to LDCs would need to be that would be equivalent in to the transfer implied by existing preference programs. They conclude that for LDCs the figure is $266

> 24 The income effects are mirrored in the trade effects in Table 4, which reveals that export reductions map to income reductions. This is fully consistent with our earlier discussion centered on Figures 2 and 3. 25 As discussed further in the concluding section a case can be made that even if exporters do not get the rents they _should_ get them. In any discussion that focuses on offsetting the loss from preference erosion one can argue that account should be taken of any “missing” rents.

19
characteristics, (iii) the local income level, (iv) the local institutional environment, and (v) the efficiency of government bureaucracy.<sup>9</sup> At the simplest level, we can classify three possible theories of government facilitation. The first is _random facilitation_ in which the local government facilitates loans and provides information randomly (and firms randomly seek such assistance). If this theory is true, we would expect no significant patterns in the relationship between government facilitation and the list of determinants mentioned earlier. A second theory is _facilitation in exchange for rents_ . Similar to the capture theory (Stigler 1971, Peltzman 1976), this theory suggests that government grants information facilitation and loan help to firms that can provide more rents to the government. It would predict that government facilitation is more likely for larger firms because they can most affect employment (a key goal of the government), for state-owned firms in order to protect less efficient firms and due to their long-run relationships with the government, and in places with more corruption and worse institutions. The third theory is _facilitation for efficiency,_ which posits that government facilitation is more likely where efficiency gains are likely to be greater. It implies a greater likelihood of government facilitation for younger firms who likely need more assistance, for non-state firms who tend to have less established relationships with state-owned banks, for larger firms in which the same facilitation may yield a larger benefit due to scale economies, for firms with stronger CEO leadership in which the same facilitation may yield a larger benefit, and in locations with better institutions since those institutions constrain government officials and channel government facilitation into more efficient activities.

Both the conjecture of facilitation in exchange for rents and that for efficiency imply that local leaders’ tenure in their positions matters. Since local party secretaries tend to have short tenures, on average 3 to 4 years on the job (Lu and Liu 2013), more experienced secretaries may be better able to provide that facilitation. At the same time, party secretaries with longer tenures are also more likely to behave like stationary bandits to internalize the benefits of such facilitation (Olsen 2000). Under either scenario, government facilitation should be more likely in locations with longer-serving party secretaries.

The results in table 5 are mostly consistent with the facilitation-for-efficiency conjecture. Many variables related to firm characteristics and the local political and institutional environment are statistically significant, which refutes the random facilitation hypothesis.

> 9 The results based on probit are very similar.

9
Policy Research Working Paper 8397

# **Abstract**

This paper details the results from the first comprehensive survey of private firms across major urban areas in the Syrian Arab Republic—including Aleppo, Homs, Hama, Latakia, and Damascus—since the conflict began in 2011. This builds on the World Bank’s Enterprise Survey from 2009 and attempts to survey each of the 508 firms from 2009 again. The survey highlights the major challenges facing firms in Syria today, such as access to electricity, fuel, and water. Yet, loss of workers, managers, and supply chain relationships are also notably severe. Rebuilding the social and human capital of Syria may be even more difficult than the bricks and mortar. The paper also identifies the ways firms have been affected in their prices, sales, supply chains, taxation, and costs as well as how they have adapted in financing and employment. These constraints and impacts are also analyzed at the subnational level and across sectors. Firms in Aleppo stand out for their uniquely difficult challenges and responses that are sometimes at odds with the rest of the country. Finally, the paper analyzes firm exit from 2009 to 2017 and finds that higher productivity firms from 2009 were more likely to survive, except in Aleppo where the reverse holds. The paper hypothesizes that productive firms facing the particularly severe destruction in Aleppo may have made a different calculation compared with productive firms elsewhere: to use their capabilities to leave rather than to use their capabilities to weather the storm.

This paper is a product of the Finance, Competitiveness and Innovation Global Practice. 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 ksalmon@worldbank.org, nassaf@worldbank.org, and dfrancis@worldbank.org.

_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
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all the simulations with a high and low estimate of the wage distortion, while leaving the value of all other parameters unchanged. For tht high (low) simulations, we used Krueger and Summers' estimates of the wage distortion plus (minus) two times the standard error of their estimate of the wage distortion. After rounding, this yields wage distortion values of 33 and 19 percent in steel and 32 and 22 percent in autos. As expected, the second best effect of superior labor reallocation is increased (decreased) with higher (lower) assumed wage distortions. The change in the estimated welfare cost estimates with increased or decreased wage distortions is always less than $35 million in both autos and steel. For example, with CRTS in autos and exogenous wage distortions, the estimated distortion costs increase (decrease) from $1.78 billion to $1.81 ($1.75) in the high (low) wage distortion case. From tables 3 and 4, one can see that $35 million is less than two percent of the distortionary costs of the auto VERs, and is also a small percentage of the total costs of the auto or steel VERs. Since the distortion costs of steel VERs are small or negative in some cases, an additional $25-35 billion of benefits from superior labor reallocation in the high wage distortion case is important in percentage terms. We conclude that, overall, the striking result is that even with high wage distortions, the benefits of labor reallocation are small relative to the costs of protection.191

# 5. The Non-Optimality of *Optimal' Policies

We now ask what are the gains from removing the wage premia and give illustrative calculations of the potential benefits from applying 'optimal' policies to counteract the distortions that arise from wage premia and/or market imperfections under IRTS. Start with the welfare gain of removing the