rafmacalaba/data-use-mentions-extended huggingface dataset:
Russia’s use of pre-shipment inspections and other formalities is high by international standards, as is its use of price-control measures. As Figure 3 shows, the frequency ratio for pre-shipment inspections and other formalities<sup>24</sup> (UNCTAD category C) exceeds 90 percent for most product categories, as does the frequency of price-control measures, such as additional taxes and charges (UNCTAD category F). These measures are relatively uncommon for other countries—frequency ratios for pre-shipment inspections and other technical measures are typically under 20 percent in most countries, while frequency ratios for price control measures are typically under 10 percent.<sup>25</sup> The data may understate the use of other formalities— requirements to pass through specific ports for customs are reported to be numerous and burdensome<sup>26</sup> but do not appear in the UNCTAD data.

SPS measures in Russia and the ECU extend well beyond agriculture. It is customary for most countries to have SPS measures for the majority of agricultural imports (HS 01-24), but Russia also has SPS measures for many chemical products; plastic and rubber products; hides, skins, and leather; wood and wood products; and textiles (Figure 3), for which SPS measures are rare internationally—the EU profile is presented as a comparator. The appearance of SPS measures in some of these unusual categories is reflected elsewhere in the ECU, in particular Kazakhstan.

While there are some cases in which SPS measures may be appropriate in non-food sectors (e.g. for pests that may travel in wood products), it is not clear why Russian SPS measures have such a broad coverage. Since many of these measures are for products not intended for human consumption, and not usually subject to quarantine risk, there is the potential that some of these measures could lead to frictions with trading partners and may be vulnerable to WTO challenge.

The profile of Russia’s technical barriers to trade is similar to that of the EU.
China: internal migration. _The encyclopedia of global human migration_ . Colas, M. and Ge, S., 2019. Transformations in China’s internal labor migration and hukou system. _Journal of Labor Research_ , _40_ (3), pp.296-331.

Comin, D., Lashkari, D. and Mestieri, M., 2021. Structural change with long‐run income and price effects. _Econometrica_ , _89_ (1), pp.311-374.

Costa, F., Garred, J. and Pessoa, J.P., 2016. Winners and losers from a commodities-for-manufactures trade boom. _Journal of International Economics_ , _102_ , pp.50-69.

David, H., Dorn, D. and Hanson, G.H., 2013. The China syndrome: Local labor market effects of import competition in the United States. _American Economic Review_ , _103_ (6), pp.2121-68.

De Brauw, A. and Giles, J., 2017. Migrant opportunity and the educational attainment of youth in rural China. _Journal of Human Resources_ , _52_ (1), pp.272-311.

Dix-Carneiro, R. and Kovak, B.K., 2017. Trade liberalization and regional dynamics. _American Economic Review_ , _107_ (10), pp.2908-46.

Duarte, M. and Restuccia, D., 2010. The role of the structural transformation in aggregate productivity. _The Quarterly Journal of Economics_ , _125_ (1), pp.129-173.

Eberhardt, M., Helmers, C. and Yu, Z., 2011. Is the dragon learning to fly? An analysis of the Chinese patent explosion. _An Analysis of the Chinese Patent Explosion (November 29, 2011). The University of Nottingham Research Paper_ , (2011/16).

Ebenstein, A., Harrison, A., McMillan, M. and Phillips, S., 2014. Estimating the impact of trade and offshoring on American workers using the current population surveys. _Review of
strategic position does not seem to have been exploited, however. The development of the sector has been driven by the economic strategy of Djibouti Telecom (DT) - the single national fixed and mobile operator to provide ICT services.<sup>1</sup> DT has a monopoly in all telecommunications markets, including those that are typically open to competition such as mobile and data services. It represents a significant portion of the economy, with revenues accounting for around 6 percent of GDP.<sup>2</sup> DT’s strategy is outward oriented, selling much of its capacity on the international market, mainly to Ethiopia. The operator has banked on the country's geostrategic position between the Middle East and Africa to successfully become a reliable offeror of connectivity between the two regions for global communications carriers. Unfortunately, this approach has not been equally matched by efforts to expand broadband access and use in the domestic market. DT’s bandwidth is not widely offered to consumers and businesses locally, leaving the domestic market in shortage.

In 2016, Djibouti ranked 161<sup>st</sup> of 175 countries in the ICT Development Index published by the United Nations International Telecommunications Union (ITU),<sup>3</sup> the last place among lower

> 1 The only two other countries in the world with a single operator are Ethiopia and Cuba. The Democratic Republic of Korea introduced a second mobile operator in 2015.

> 2 Source: World Bank, Telecommunications Sector in Djibouti: Finding the Path to Growth, 2015 (p.6).

> 3 See http://www.itu.int/net4/ITU-D/idi/2016/#idi2016countrycard-tab&DJI.

2
some transportation services, butane and natural gas, and banking transactions are also exempt, causing an erosion of the tax base. In FY13 the effective tax rate on the GST was 7.1 percent.<sup>19</sup>

**Figure 5. Tax Revenues as a percent of GDP** , **Egypt and Comparison Countries**

<!-- Start of picture text --> 30%<br>25%<br>20%<br>15%<br>10%<br>5%<br>0%<br>India Indonesia Egypt Malaysia Jordan Turkey Morocco South Africa<br>Source: IMF International Financial Statistics Database (http://data.imf.org/?sk=4C514D48-B6BA-49ED-8AB9-<br>52B0C1A0179B&sId=1390030341854 )<br><!-- End of picture text --> The income tax suffers from problems of its own. It is also affected by the informal sector and low tax collection. In 2015, the government implemented some reforms to the income tax, increasing the

> 17 And 12.5 percent in FY15.

> 18 Measured in PPP (constant 2011 international $). Source: WDI, accessed August 9, 2018.

> 19 Due to limited data, this is the most recent estimate.

15
**Table A.3.4: Per student average earnings loss in annual terms by region, income group, and lending type**

|||Post-COVID-19<br>||
|---|---|---|---|
|Aggregate|Optimistic|Intermediate|Pessimistic|
|EAP|382|945|1,529|
|ECA|568|1,482|2,433|
|LAC|242|534|835|
|MNA|457|1,111|1,789|
|NAC|654|1,838|3,075|
|SAR|116|216|319|
|SSF|130|252|375|
|Grand Total|355|872|1,408|
|HIC|672|1,865|3,110|
|UMC|332|676|1,029|
|LMC|160|301|443|
|LIC|72|127|183|
|Grand Total|355|872|1,408|
|Part I|716|1,981|3,301|
|IBRD|316|668|1,030|
|IDA/Blend|114|214|316|
|Grand Total|355|872|1,408|

Source: Authors’ calculation. Decrease on average annual earning per student (2017 PPP $). Simulation 1 results based on latest available LAYS of 157 countries (unweighted average), with the change in LAYS expressed in foregone future annual earnings per student.

48
marginal effect in our sample.

An interesting question is whether beyond the significant negative contemporaneous effect of price distortions on economic growth there is also a significant negative lagged effect. A lagged effect could arise if, for example, there are significant adjustment costs to capital that differ across sectors in the economy. Our panel data set has a fairly large _T_ dimension (the average _T_ is about 35) and, therefore, is well suited to explore lagged effects of within-country changes in policy distortions to relative agricultural prices on economic growth. In fact, it is worth to restate here that a key advantage of using annual panel data is that this allows us to examine not only short-run growth effects, which are of substantial interest in and of themselves, but also medium/long-run growth effects by means of a distributed lag model.

In Table 7 we report dynamic panel data estimates as a first approximation to characterize the medium/long-run effect of relative agricultural price distortions on economic growth. It is well known that the presence of country fixed effects leads to inconsistent least-squares estimates in the dynamic panel data specification. Yet in our regressions this fixed effects bias should be relatively small since the average _T_ is fairly large. To check whether this fixed effects bias is indeed small in our regressions, we report, in addition to least squares estimates, system-GMM estimates (Blundell and Bond, 1998). For these system-GMM estimates, we use the first lag as an instrument to ensure that not too many moment conditions are used.

Panel A of Table 7 shows that the dynamic panel data regression produces a coefficient on lagged GDP per capita growth of about 0.05 to 0.1. A test for second-order serial correlation produces insignificant results in all cases. Thus, specification tests indicate that the model is well specified. We compute the long-run growth response from the dynamic panel data model by inverting the characteristic polynomial. This yields a cumulative (long-run) growth effect of a permanent increase in relative agricultural price distortions of about -0.05
7 We have already mentioned that at the beginning of the 80's real (ex post) "market" lending rates were negative, even in the absence of subsidies. They became positive, on average, until 1987, and negative again in the following two years, following the earthquake and a period of fiscal laxity, resulting in a fall in the M2 to GDP ratio. In the 1990's real rates have been mostly positive and increasing (see Figure 2). Interest on directed credit programs like FOPEX and others administered by CFN were significantly lower than lending market rates, as Table 4 shows. Market rates were 1.58 times the subsidized ones in 1983, 1.94 times in 1988 and only 1.19 times in 1991. The spread between-the two was 21.57 percentage points in 1988 and 8.82 percentage points in 1991.

# **III.-** FIRM LEVEL EVIDENCE ON ACCESS TO LONG TERM DEBT AND ON DEBT MATURITY

In this section we will discuss the micro level evidence on the maturity structure of firms' financing. We use two samples in our analysis.<sup>5</sup> Both of them are based on accounting data collected by the Superintendencia de Companias. The first (unbalanced) sample (SCI from now on) includes 731 Ecuadorian manufacturing companies during the period 1984-1988 and contains more detailed information on firms' real and financial variables. Moreover, for the companies in this sample we have been able identify whether they belong or not to an industrial group with bank association. For this sample we have available separate figures for short term (non trade) debt, long term debt, and trade debt, 5See the Data Appendix for a description of the data.
logit model are reported. Sample is restricted to males aged 20-59. Agr. is short for agriculture, Manu. is short for manufacture, Cons. is short for construction, and Serv. is short for service. To combine the HIES and the RMS sample in Columns 1-4, sample weights are applied. Data source: Bangladesh HIES 2016 for nonmigrants and RMS 2018-19 for return migrants; Nepal LFS 2017-18; Pakistan LFS 2014-15 and 2017-18. * p _>_ 0.1, ** p _>_ 0.05, *** p _>_ 0.01.
30 remains unclear whether bargaining among multiple coalition partners in parliamentary systems regarding particular proposals is less costly than bargaining between only two veto players in presidential systems. The DPI data set, however, provides one tool for advancing research on this question.

The extent to which one political decision maker might act as a check on another depends in part on the similarity of their policy preferences. Government decision makers are more likely to exercise strong veto power if their policy preferences are closer to those of the Opposition and more distant from the preferences of other government decision makers. Such a decision maker would be more willing to leave the government and join the opposition than decision makers whose views were far from the opposition. To take into account the policy orientation of parties, a second checks and balances variable, CHECKS2, was therefore compiled and introduced into the data set. CHECKS2 is therefore the same as CHECKS1, but is augmented by one for every veto player (defined as the largest government party in the legislative chamber in presidential systems, and all coalition members in parliamentary systems) whose orientation (left, right or center) is closer to the opposition’s orientation than to the average of the rest of the government. The opposition’s orientation is given by the orientation of the largest opposition party. |

These new measures of checks and balances offer.considerable additional information - about polities. Their correlation with the coding of Index of Political Cohesion in the database is less than 0.60. This suggests that theoretical priors about the number of veto players in government can make a significant difference for empirical work, reinforcing the need for diverse data sets and variables.
............................. 12|
|Figure 5: Distribution of monthly per capita expenditure, nominal and spatially adjusted ....................... 17|
|Figure 6: Distribution by governorate and quintiles of spatially adjusted and nominal monthly per capita<br>expenditure ................................................................................................................................................. 17|
|Figure 7: Governorate level poverty estimates based on nominal and spatially adjusted welfare ........... 18|
|Figure 8: Poverty estimates based on HNAP 2022 data, nominal aggregate ............................................. 18|
|Figure 9: GDP deflator and CPI growth index (2003=100) .........................................
due to inadequacy in the distribution infrastructure. In addition, there is a risk that poorer households could opt out disproportionately if they are required to pay for vaccinations.

> 29 - <u>Results of Mongolia COVID 19 Household Response Phone Survey (Round 3).</u> January 2021.

> 30 <u>Indonesia High-frequency monitoring of COVID-19 impact (brief for round 4). January 2021.</u>

> 31 According to estimates in that report, 10-percentage point higher vaccination coverage was associated with a one-half of a percentage point higher quarterly gross domestic product growth.

27
. Mendes (2025). Inventory decisions under political violence. _Economics Letters 247_ , 112158.

- De Chaisemartin, C., X. d’Haultfoeuille, F. Pasquier, D. Sow, and G. Vazquez-Bare (2022). Difference-in-differences estimators for treatments continuously distributed at every period. _Mimeo_ .

- De Chaisemartin, C. and X. d’Haultfoeuille (2020). Two-way fixed effects estimators with heterogeneous treatment effects. _American Economic Review 110_ (9), 2964–2996.

- De Roux, N. and L. Martinez (2023). Uncertainty, peace, and investment: Evidence from credit microdata in Colombia. _Mimeo_ .

- Del Prete, D., M. Di Maio, and A. Rahman (2023). Firms amid conflict: Performance, production inputs, and market competition. _Journal of Development Economics 164_ , 103143.

26
in those regions furthest away from the technological frontier such as Sub-Saharan Africa, which until now tended to have lower ICT adoption rates and underdeveloped ICT infrastructure.

This paper has analyzed empirically firm level ICT adoption in six African countries using freshly collected data from the Enterprise Surveys innovation modules. The data suggest that most African firms are still lagging behind ICT adoption rates as compared with firms in developed countries. However, when looking at specific countries in the sample, the data show a very heterogeneous picture; some countries, such as Kenya, show high ICT adoption rates and others, such as DRC and Tanzania, have low ICT adoption, which is in line with their income per capita level.

Given this ICT adoption heterogeneity, it is important to measure what impact this is having on firms’ innovation capabilities and productivity. ICT can act as an enabler for the introduction of new processes or new products, which in turn can have a positive impact on productivity. Thus, in the second part of the paper, we have measured empirically the impact of ICT on innovation outcomes and productivity.

Regarding ICT use, the findings of the paper suggest that larger, younger, more internationalized –foreign owned, importers, certified and with foreign technology license – firms, which are financially unconstrained and operate under higher degrees of competition, are more likely on average to use ICT. This suggests the

> 17 These estimates are available upon request.

> 18 As only few firms have introduced a new product or process to the international market in these six countries as a whole, it is not feasible to estimate at the country level.

35
Table 13: Falsification Exercise: Determinants of Living in an Extended Family - Albania (2002 - 2012)

|||Dependent|Variable:||
|---|---|---|---|---|
||Livi|ng in an Ex|tended Fa|mily|
||(1)|(2)|(3)|(4)|
|Boy frst|0.0065|0.0247|0.0159|0.0064|
||(0.0131)|(0.0165)|(0.0110)|(0.0159)|
|Boy second|-0.0002|0.0180|0.0092||
||(0.0167)|(0.0156)|(0.0114)||
|Two girls|-0.0187|||-0.0186|
||(0.0228)|||(0.0156)|
|Two boys||-0.0176||0.0004|
|||(0.0227)||(0.0166)|
|Samesex|||-0.0091||
||||(0.0114)||
|R-squared|0.2982|0.2665|0.2982|0.2982|
|Observations|7404|7404|7404|7404|
|Mean dep. var|0.381|0.381|0.381|0.381|
|Survey FE|Yes|Yes|Yes|Yes|
|District FE|Yes|Yes|Yes|Yes|
|Controls|Yes|Yes|Yes|Yes|

_Notes:_ Standard errors clustered at the PSU level are in parentheses. Other covariates in the models are the following: _Age, Age Squared, Age at First birth, Years of Education_ and also indicators for _Boy 1st_ and _Boy 2nd_
The secondary sector also picked up, from 2.9% per annum to 4.5%.<sup>39</sup> So too did the primary sector, but at a much lower level; the pre-1991 growth rate in primary NDP per capita was only 0.2% per annum, while it rose to 0.8% in the post-1991 period.<sup>40</sup> As one would expect, the share of the primary sector in NDP has fallen appreciably from 55% in the early 1950s to 15% in 2012.

The acceleration in survey-based mean real consumption growth—from 0.6% per annum in the pre-1991 period to 2.0% in the post-1991 period—is significant. The urban and rural trends reveal a pattern that is similar to the national level, though there are some differences between the two segments of the economy (Table 2). The NSS mean consumption growth rates are appreciably higher (nearly twice as high) post-1991 in both rural and urban areas.

Faster growth post-1991 has also come with rising inequality within urban areas, but less so in rural areas. Figure 2 plots the indices over time. Note that these are the “raw” values, without adjustment for the effect of MRP rounds. When we add controls for MRP rounds, we also see rising inequality in rural areas post-1991. Table 2 gives the exponential trends for the Gini index. In contrast to a declining trend in rural Gini and no trend in urban Gini in the pre1991 period, a significant positive trend in inequality emerged post-1991 in both sectors. The rise in inequality has been greater in urban areas. At the same time, inter-sectoral inequality has been generally rising. We see from Figure 3 that the ratio of urban mean to the rural mean has been rising since around 1970 (the early observations were volatile, and should probably be discounted), though with signs of levelling off and even decline since 2000. Controlling for MRP rounds, time trends
using data from the program‘s information system for impact evaluation purposes, this paper highlights the opportunities for research that may arise from using monitoring and evaluation systems, as these are becoming increasingly popular tools to administer CCTs and other safety net programs. Finally, this paper also investigates the extent to which the final educational outcomes of older children that are not eligible to the program could be influenced by the participation of their siblings.

> 5 Treated children were then matched to children in the control group based on the propensity to stay in school, derived from those in the control group that were enrolled both before and after program implementation.

> 6 Schools could be comprised of children that take the test and others that do not take the test.

8
<!-- Start of picture text --> SECTION 5A:Infrastructure (roads/bridges/culverts) availability and condition<br>Type of road/bridge/culvert Does this sub- What is the total INTERVIEWER: IS THIS What is the current state of | In your opinion, what is the main reason for<br>county have any length of [ROAD] NUMBER BASED ON the [ROADS}/bridges? the poor roads?<br>COMPLETE COLUMN 5 [ROAD]? within sub-county RECORDS OR SUB-COUNTY<br>BEFORE MOVING ON TO (km)? CHIEF ESTIMATIONS? 1=Good (>>NEXT) 1=Bad weather<br>FOLLOW UP QUESTIONS 1=Yes 2=Usable (>>NEXT) 2=Lack of equipment<br>2=No (>>NEXT (FOR BRIDGES/ 1=Based on written records 3=Poor 3=Poor maintenance<br>ROAD) CULVERTS 2=Based on respondent 4=Lack of engineers<br>Re SsGGRECORD NUMBER) estimation 8=Other<br>[3 [Feeders PP<br>[4 [communiyroats ff ee<br><!-- End of picture text -->

|SECTION 5A:Infrastructure|(roads/bridges/culve|rts) availabilityand c|ondition|||||
|---|---|---|---|---|---|---|---|
|Type ofroad/bridge/culvert<br>COMPLETE COLUMN 5<br>BEFOREMOVING ON TO<br>FOLLOWUP QUESTIONS<br>|Does this sub-<br>county have any<br>[ROAD]?<br>1=Yes<br>2=No (>>NEXT<br>ROAD)<br>|What is the total<br>length of [ROAD]<br>within sub-county<br>
listed on the Prague Stock Exchange (PSE). It is compiled on the basis of a questionnaire sent to firms by Aspekt a.s.. Starting from the first year of the survey (1992) the financial variables were defined using international accounting standards. Thus the switch to international accounting standards in only 1994 in the reporting of firms to the National Statistical Office does not affect our data-series. A number of firms do not report PSE-prices since their shares are not actively traded. The Aspekt database defines such firms as firms whose shares trade less than four times in any given year. We exclude such firms from our analysis. The 1992-95 data are complete for 371 firms which went through the first wave of voucher privatization. An additional set of 355 firms which went through the second wave report consistently after 1993, making altogether for 706 firms in the period 1993-1995.

Summary statistics on the ownership structure of the firms are presented in Table 1, Panel A. Six investor classes are distinguished: the state,' individuals, bank and non-bank sponsored IPFs, dlomestic direct and foreign direct investors. The ownership stakes of the major bank sponsored funds are listed separately in Table Al. Several banks have sponsored more than one 7. Shares held by the National Property Fund (through permanent, temporary and restitution shareholdings), shares to be sold through banks, and shares not sold.