rafmacalaba/datause-encoder-data huggingface dataset:
> timeliness variable with a dummy<sup>_I_</sup> _g_<sup>that equals 1 if</sup> _X ijg_ are exports of intermediate goods and 0 otherwise. In creating these interaction terms we center the variables at the sample mean in order to facilitate the interpretation of results.  We run equation (2) twice: in the first case, we pool the exports of intermediate and consumption goods, and in the second case, we pool the exports of intermediate and all other goods (consumption and capital goods). We are most interested in the coefficients β4 and β6. A positive estimate of these parameters would provide evidence consistent with the general assumption of theoretical models of trade that the hold up problem and timeliness are particularly important as a source of comparative advantage in intermediate goods than in consumption goods.

We address potential endogeneity problems arising from omitted variables problems or from reverse causality. A concern is, for example, that trade (specialization) in institutional-intensive sectors could stimulate institutional reforms or that trade in time-sensitive sectors could foster investments in transport infrastructure. To address these issues, first, we adopt a factor content methodology that, as noted in Djankov, Freund and Pham (2010), presents the advantage that it minimizes identification problems. Second, we use country and industry fixed effects in all regressions to minimize omitted variable bias. Third, we also use instrumental variables (IV) estimations. In particular, we use the legal origin of a country’s legal system as an instrument for quality of institutions, and, focusing on a subsample of landlocked countries, we use the average quality of infrastructure of its neighboring countries as an instrument for the quality of infrastructure of each landlocked country. The results of instrumental variables regressions and other robustness checks are presented in section IV.

# **III.  Data Sources and Variable Definitions**

Data on trade flows, factor endowments and factor intensity are from standard sources. The year under consideration is 2000. Exports data at the SITC Rev. 3 5-digit level are from the OECD/UN International Trade Commodity Statistics (ITCS) database. We use the UN Broad Economic Categories (BEC) classification to define intermediate goods. We then map these data to 6-digit NAICS 1997 industries using the correspondence table from Feenstra et al. (2002). The BEC classification groups products into four categories of goods according to their main end use, i.e. intermediate, consumption, capital goods and not classified goods.<sup>8</sup> The world share of trade in terms of these four categories is reported in Table 1. As shown in the table, intermediate goods are the most important component of world trade both in terms of volumes and number of products.

> 8 This residual category includes for example passenger motor vehicles. Passenger motor vehicles are not classified by BEC because they are used as capital goods when purchased by a company to run its businesses, whereas they are used as consumption goods when bought by private households.

6
by-country difference-in-differences). Column (2) reports the results from restricting the sample to AGOA suspended countries. The treatment group is AGOA eligible products, with AGOA ineligible products representing the control group. The AGOA suspension effect becomes −26 percent and continues to be statistically significant. The estimated impact from product-level difference-in-differences is smaller possibly due to the presence of favorable shocks to AGOA eligible products that coincided with the suspension from AGOA. In column (3), the sample is restricted to AGOA eligible products. This specification identifies the AGOA suspension effect from the relative drop in exports from suspended countries (treatment group) versus non-suspended countries (control group). The AGOA suspension effect is higher at −47 percent. In both standard difference-in-differences specifications, the AGOA expiration effect remains negative and significant. However, product-level difference-in-differences underestimates while country-level difference-in-differences overestimate the effect. Hence, the rest of the paper proceeds with the triple-difference specification employing the full sample of AGOA eligible countries and all products.

To estimate the impact of AGOA suspension on the extensive margin, the dependent variable is replaced with a dummy that takes the value of 1 when the exports are positive and zero otherwise. As reported in column (4), the probability of a suspended country exporting an AGOA eligible product to the US decreases by 2 percentage points after the suspension. The impact of AGOA suspension on the extensive margin is much larger than that reported in Hakobyan (2020) that examines the effect of withdrawal of GSP benefits.

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(1982, 1988) negotiated after the enlargement of the EU in 1981 and 1986. This implies that liberalization will mostly occur on the Tunisian side. As discussed below, the area where Tunisia potentially stands to gain significantly in terms of greater export opportunities--agriculture--was largely removed from the table. Quotas are to be abolished upon the entry into force of the agreement--except as allowed by GATT rules. In contrast to the CEEC Agreements, no special treatment was given to Tunisia as regards more rapid elimination of textile quotas than agreed under the GATT. However, Tunisia is reportedly only subject to two quotas, neither of which is close to being fully utilized (World Bank, 1994). Tunisia committed itself to gradually reducing tariffs on industrial products of EU origin to zero. Five groups of products--at the 7-digit Community Common Nomenclature (CN) level--have been defined in this connection. Four of these groups have been defined explicitly in Annexes. Tariffs for the fifth group, the residual (i.e., manufactured product that are not mentioned in one of the Annexes) will be abolished upon the entry into force of the agreement. There are 470 6-digit tariff lines in this group, all of which are either intermediate inputs or machinery (capital goods), accounting for 10 percent of 1994 imports from the EU (Table 4). **12** Annex 3 to the Agreement contains a list of products for which tariffs and surcharges will be eliminated over a 5 year period in steps of 15 percent, starting from the entry into force of the treaty. Products on this list, together with the group of goods to be liberalized immediately (i.e., those not mentioned in an Annex) account for some 35 percent of 1994 imports by Tunisia. Annex 4 comprises a list of products that will be liberalized over the full 12 year period transition period, in steps of 8 percent per year. Products listed in Annex 5 will commence tariff reductions four years after the entry into force of the agreement, with reductions spread out linearly over the remaining 8 years of the transition period (i.e., annual cuts of 11-12 percent). A final list of manufactured products contained in Annex 6 is exempted from tariff reductions. This list contains 37 6-digit tariff lines, comprising bread, pasta, and carpets.

> 12 Trade data reported by EUROSTAT is either on a 6 or 8-digit level basis, making it impossible to relate exactly the tariff commitments (which use 7-digits) to publicly available trade statistics. However, in most cases, a concordance from the 7 to the 6-digit level was straightforward.

15
Policy Research Working Paper 8078

# **Abstract**

There is relatively little systematic evidence on the links between procurement systems and outcomes such as competition and corruption levels. This paper adds to the evidence base, using data on almost 34,000 firms from the World Bank’s Enterprise Surveys, in 88 countries that also have procurement systems data from Public Expenditure and Financial Accountability (PEFA) assessments. The analysis finds that in countries with more transparent procurement systems, where exceptions to open competition in tendering must be explicitly justified, firms are more likely to participate in public procurement markets. Moreover, firms report paying fewer and smaller kickbacks to officials in countries with more transparent procurement systems, effective and independent complaint mechanisms, and more effective external auditing systems. These findings—particularly on kickbacks—are robust to the inclusion of many controls and to a range of sensitivity tests. The study finds evidence that better procurement systems matter more for smaller firms’ participation in procurement markets and payment of kickbacks to obtain contracts, consistent with the view that information and transactions costs that are incurred in learning about bidding opportunities and fulfilling bidding requirements are more onerous for smaller firms. Falsification tests show that other, non-procurement indicators from the PEFA assessments are not associated with procurement outcomes, and that the PEFA procurement indicators are not strongly associated with other “governance”-related outcomes in firm surveys that are unrelated to procurement.

This paper is a product of the Macroeconomics and Growth Team, Development Research Group. 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 sknack@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
<!-- Start of picture text --> Period -5 Period -4 Period -3<br>.32 .17<br>.315<br>.165<br>.31<br>.31<br>.16<br>.305<br>.3<br>.155<br>.3<br>.15<br>.29 .295<br>-20 -10 0 10 20 -20 -10 0 10 20 -20 -10 0 10 20<br>Normalized annual Normalized annual Normalized annual<br>accumulated consumption accumulated consumption accumulated consumption<br>Period -2 Period -1 Period 0<br>.08<br>.075 .1<br>.075 .07 .095<br>.07 .065 .09<br>.06<br>.065 .085<br>-20 -10 0 10 20 -20 -10 0 10 20 -20 -10 0 10 20<br>Normalized annual Normalized annual Normalized annual<br>accumulated consumption accumulated consumption accumulated consumption<br>Ratio of consumption to annual accumulated consumption in 0 Ratio of consumption to annual accumulated consumption in 0<br>Ratio of consumption to annual accumulated consumption in 0 Ratio of consumption to annual accumulated consumption in 0<br><!-- End of picture text --> Figure 3 Ratio of Consumption to Anual Accumulated Consumption in Period 0 _Notes:_ Scatter points correspond to local averages computed by bins with a bandwidth of 1 unit of normalized AAC. Solid lines correspond to parametric fits generated from regressions that include a constant, a treatment dummy and a linear term for normalized AAC. Dashed lines are the 95% confidence interval.

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2009). Trade policy as a protectionist device has not been seen to play a big role in the global collapse of trade, neither as a cause nor a consequence. Nevertheless, anecdotal evidence suggests that some countries are actively tinkering with their trade policies. For example, during the crisis period, Bolivia and Ecuador are shown to have altered their tari¤s on a large share of their imported products (Gamberoni and Newfarmer, 2009), while India is documented to have increased its use of anti-dumping (AD) duties (Bown, 2009b). How important are those changes in explaining or prolonging the collapse in world trade? The objective of this paper is thus to carefully compare the trade policies of a wide range of countries over the crisis period, and to assess by how much trade may have fallen due to the increase in tari¤s and AD duties of these countries. To be clear, for the purpose of this paper, we narrowly de...ne trade policies to only include tari¤s and AD duties.

To achieve our objective, we obtained the Most Favored Nations (MFN) applied tari¤ schedules and the bilateral tari¤ schedules for a wide range of countries in 2008 and 2009.<sup>1</sup> The MFN applied tari¤s tend to over-estimate the level of protection because they do not account for the existence of bilateral or regional tari¤ preferences. Hence, it is important for us to construct the OTRI based on the bilateral tari¤ schedules. This signi...cantly complicates the calculation of the OTRI as each country may have up to 200 trading partners and each bilateral tari¤ schedule consists of nearly 5000 HS 6 digit products. To spice up the tari¤ policies, we also merge the bilateral tari¤ schedules with the World Bank Global Anti-dumping Database, maintained by Chad Bown (2009a).<sup>2</sup> Thus, changes in the OTRI re‡ect both the changes in tari¤s and AD duties during the crisis period.

In addition, we need bilateral import demand elasticities and bilateral trade ‡ow data to prop-

> 1 We are extremely grateful to Mr. Mimouni Mondher from the International Trade Center in Geneva for kindly sharing the data with us, and to Richard Newfarmer and Elisa Gamberoni for facilitating the request.

> 2 We are highly indebted to Chad Bown for his suggestion to include the AD data in our calculations. He also graciously shared the latest data with us for this project.

2
the language and mathematics assessments for teachers included test items starting at grade 1 level (simple spelling or grammar exercises, addition and subtraction) and included items up to the grades at the upper primary level (Cloze passages to assess vocabulary and reading comprehension, interpretation of information in a diagram and/or a graph, and a more advanced math story problem).<sup>13</sup> The teacher tests have good reliability, with a reliability ratio (estimated by Cronbach’s alpha) above 0.85 in both subjects on the teacher test. Like the student tests, the teacher test scores used here are based on IRT-derived ability scores for each of the assessments, and they are normalized to have a mean of 0 and standard deviation of 1 across all grade 4 teachers in these six countries.

In addition to these tests, we also incorporate data from a teacher roster, a classroom observation of a lesson, and from a module that measures teacher absence. The teacher roster collects basic demographic and education background information on teachers: age, gender, highest education level completed, whether the teacher holds a teaching certification,<sup>14</sup> whether they were born in this district, as well as the teacher’s contract status.<sup>15</sup> We also use information on whether the school is in an urban or rural area.

In each school, one grade 4 lesson was observed for its entirety. During this classroom observation, enumerators recorded minute-by-minute what the teacher was doing against a set of predefined activities. Activities include descriptors such as “Teacher interacts with all children as a group” or “Teacher supervises pupil(s) writing on the board” or “Teacher in class - not teaching.” We use these data to construct a measure of the share of time the teacher is teaching. After the lesson, enumerators record what they observed along three main dimensions: the teacher’s general demeanor; the use of what are generally thought of as good pedagogical practices; and observations on the classroom environment. For each of these sets of variables, we code responses as a series

> 13 Cloze sentences/passages leave blank a word in a phrase/sentence and ask the test-taker to fill in that word (sometimes from a set of options) with one that completes the sentence in a way that is sensical and grammatically correct.

> 14 The specific teaching certification varies across countries, which is why we focus only on having one versus not having one.

> 15 For Madagascar, Mozambique, Tanzania, and Togo, “permanent” contract status teachers are those who are reported as being “Government official” whereas non-permanent are those who are reported as “Government nonpermanent,” “Volunteer,” “Private contract,” “Financed by the community,” “No contract,” or “Other.”  For Kenya and Uganda, “permanent” contract status teachers are those who are reported as being “Owner/Director,” “Head teacher/principal,” “Deputy head teacher,” “Senior teacher,” “Teacher (government),” while non-permanent status are those reported as “Teacher (paid contract),” “Teacher (volunteer),” or “Other.”

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# **CONTENIN**

||EMg|
|---|---|
|Introduction<br>.al.Stud.......................................|1|
|The Role of the Public Sector--Theory**a**n the<br>Facts<br>...........................<br>2|......|
|The public sector--paradigm lost<br>.........................................|3|
|Effects on macroeconomy ..................................................||
|SpiTover effects of govemnment employment and pay.......................|...<br>8|
|Empirical Studies .................................|12|
|Effects of the public sector on the macroeconomy.....................|2|
|Impact on employment.3<br>.................................|13|
|Impact on wages<br>..................|5...............<br>2|
|The importance of nonwage benefits .<br>.................................|8|
|Data on wage compression ..........................|20|
|External effects ..............................|21|
|Conclusions and Policy Implications..........................23||
|Reforms in sector pay and employmnent.....................23||
|The political economy of reforms........................25||
|Policy implications<br>.................................|26|
|References ..................................|31|

Helpful comments from Arvil Van Adams, Jacques van der Gaag, Barbara Nunberg, and Luis Riveros are gratefully acknowledged.
41. The interest spread **Figure 12. Emerging Market Spread Compared to U.S.** (over US dollar London **High-Yield and Swap Spread, 1996-2000** Interbank Offer Rate 1 40 **1h y,.[d :p-od Oefi .- )** -.... (LIBOR)) paid by a MIC ...., **EMBl.spr.** dOi. **0 20** borrower is often significantly **200.** so higher than even the least j. 1,000 creditworthy borrowers 3 \ . - - - (issuers of 'junk bonds') in the 400 ' 1 high income countries. Figure 20, . 12 shows, for 1996-2000, the R b Emerging Market Bond Index _Source_ Bloomberg. spread indicating the borrowing costs for 11 emerging market (MIC) countries, the high yield spread paid by the least creditworthy US corporate borrowers, and the swap spread incurred by the most creditworthy borrowers in the US (i.e., the spread between AAA and AA-rated issues). Evidently, borrowing costs of emerging market issuers are both the highest and the most volatile.

42. Creditworthiness varies considerably within the MICs. This is evident from Figure 13 showing sovereign credit ratings by Moody's and spreads as of = September 2000. While borrowing ., costs (spreads) are expectedly higher for less creditworthy countries, similarly rated countries often have to pay different spreads. Borrowing costs rise dramatically as country creditworthiness deteriorates. Thus, capital becomes scarcer as the need for capital becomes more intense. Access to capital also becomes more uncertain as market perceptions get worse (Figure 14). When credit ratings are downgraded, not only - do borrowing costs go up, but also the volatility of spreads rises dramatically.

<!-- Start of picture text --> Figure 13. Credit Ratings and Spreads<br>(as of September 2000)<br>_Cre.iie,ourgESpead -<br>BatlH _ _ _.1,200<br>n.1I F]F__r<br>Bl J l H1 6nl<br>c' 400<br>---<br>li I IHWII 0<br>2 .2 o a , 1 e 5 E5 J.<br>lmvesomoogrde Below iWsOflesner, grade<br>Source Global Development Finance 2001, World Bank,<br>Figure 14. Volatility of Spreads during Crises<br>(late 1990s)<br>l<br>20 Usr,.s.<br>00<br>-<br>D o 0 5000 1.000 1.500 2,000 2,500 3.000<br>Volatility-<br>* Standard deviation of secondary market spreads of sovereign bonds<br>during January 1996-February 1999.<br>Source Global Development Finance 2000, World Bank.<br><!-- End of picture text --> 15
13 address the role of public sector pricing in adjustment policies, their conclusions are also relevant for the analysis of energy price changes.' Methodologies of analysis used in these studies fall into three subgroups. The first subgroup is based on taditional demand-oriented macroeconometric models<sup>9</sup> involving structural systems comprising behavioral equations and identities to determine aggregate output and price level through interaction of aggregate demand and supply. While differing in the degree of disaggregation of demand and supply and the extent of industrial and market detail and functional specifications of behavioral relationships, the main focus is on anabling the impacts on GNP of sudden increases in intemnational oil prices. A major limitation of these studies is the treatment of the supply side effects of the energy price changes. The second subgroup consists of energy-economy models belonging to Computable General Equilibrium (CGE) models based tially on general equilibrium theory and neoclassical theory of economic growth." The emphasis in CGE studies is to simulate the efrects on relative prices, resource allocation and welfare consequences of energy policy dcanges Lastly, there are some studies that analyze the energy price increase on a sectoral or industry basis within a partial equilibrium fimework.

_A Framework_ Economic impacts of domestic energy price increases can be categorized into two groups: (1) direct partial impacts of price increases on producers and consumers, and (2) overall macroeconomic inmpacts on price level, govenment revues and output To analyze both the micro and macro impacts and draw policy conclusions, it is importan **t** hat the framework be sufficiently disaggregated to account for differences in the demand structures of industrial and household consumers of energy. It should also be based on a consistet economywide fiamework although not necessarily an economywide modeL to allow for an analysis of macro impacts.

' **Ainrad,** P. **and** Grnis, W. (194: Macoonomic and Diriutionl Impficatis of Secord Policy **Inteein. An Applicatin** to hailand. **World Bak** Staff Woring **Papers** No. 627, **Washington,** D.C.; **Glhw,** N. **amd** S. **lhiri.** (1984): **Short-nn** Energy **Economy Ieactions in** Egypt, World Dovelopment, Val. 12, **pIp 799820; Panh,** L **d** H. **Sarar,** (1990): **Rosoum= Mobiliztioa through** Administerd Prioes **in an Endian CGB,** in **Taylor, L. ad.** (1990) Socially Relevant Policy Analysis, Manssast, The Mrr Press: World Baik (1983) **Idoesi Selcted isse** of **Ener Pcing,** Repoit No. 4285-IND, **Wahigton,** D.C.

**Hichkana** B.G., and **othe** (1987): **oom Ihpactp** of EneWr Shoch, A **_sterdam, North-Holl**

**_"0_ See Bergman, L.** (1988): **Enery** Policy Modelling; A **Survey** of **General Eqllbrnm Approchs, Joumnl** of **Policy Modeling, Vol** 10, **pp.** 377400.
- World Bank. 2015. _World Development Report 2015: Mind, Society, and Behavior_ . Washington, DC: World Bank.

- Wydick, B., P. Glewwe, and L. Rutledge. 2013. "Does International Child Sponsorship Work? A SixCountry Study of Impacts on Adult Life Outcomes." _Journal of Political Economy_ 121(2): 393– 436.

- ———. 2017. “Does Child Sponsorship Pay off in Adulthood? An International Study of Impacts on Income and Wealth.” _World Bank Economic Review_ 31(2): 434–458.

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