rafmacalaba/datause-encoder-data huggingface dataset:
cost-cutting and co-development, and sufficient security in orders to allow suppliers to justify investments in dedicated equipment and long-term worker training. Polls of American suppliers, it is worth noting, consistently show that they prefer working with Japanese assemblers precisely because the Japanese offer what the suppliers regard as a fair balance of constraints, competition and support. So far, there is little sign that Japanese-style supply relations are taking root in China. The best test case will probably come in Tianjin, where Toyota brought along a passel of its parts affiliates to supply Tianjin Xiali, now a subsidiary of FAW. In addition to the shop floor weaknesses of individual firms and the lack of an effective suppler network, Japanese critics note the weakness of crucial material inputs such as highgrade steel, engineering plastics and even rubber, but as assembly volumes have increased, investments in surface-treated cold-rolled steel and other inputs have begun to catch up.

In contrast to the Japanese obsession with the mis-organization of Chinese firms and networks, Western analysts and central government officials in China are particularly concerned about overcapacity. The consulting firm KPMG estimates that excess capacity could reach 90% of demand within a couple of years (KPMG Transaction Services 2003). The extraordinary burst of investment results not just from starry-eyed foreigners jockeying for a position in the greatest emerging market, but also from aggressive moves by local firms, many of them controlled by local and provincial governments drawn not just by rapid growth and high profitability, but also the opportunity to profit from property development and land speculation. All across China local governments are feverishly laying out new “auto parks.” In some locations, such as Shanghai, Changchun and Tianjin, clustering of auto manufacturing in one park may make sense, but the motivations and outcomes may be quite different in other locations, such as Yantai and Jinan in Shandong, Yizheng west of Shanghai, or Zhuhai, near Hong Kong (see e.g. _China Daily_ 4.25, 6.19, 6.30, 8.12.2003). Not surprisingly, authorities in the central government express great concern about moderating and rationalizing local 50
**Table 11. Economic Sector. Matching group:**<sup>**Age 17-65. Three nearest neighbors based o propensity**</sup>

|_Cohort_|_Agricu_<br>_Control_<br>_Group_|_lture, fishi_<br>_CONAL_<br>_EP_|_ng, etc._<br>_._<br>_Group E_|<br>_Control_<br>_P_|_Extraction_<br>_CONAL_||_M_<br>_Control_<br>_Group_|_anufactur_<br>_CONAL_<br>_EP_|_ing_<br>_._<br>_Difer_|_C_<br>_Control_<br>_Group_|_onstructi_<br>_CONAL_<br>_EP_|_on_<br>_D_<br>_r_|_Electric_<br>_Control_<br>**_Group_**|_ity, gas,_<br>_CONAL_<br>_EP_|_and water_<br>|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|90 - 93|1.2|0.0|-1.2|0.0|0.0|0.0|26.8|30.4|3.6|3.6|0.7|-2.9|0.0|2.0|2.0<br>|
|91 - 94|_1.5_|1.2|-0.4|0.0|0.6|0.6|24.7|33.9|9.2|_3.6_|1.8|-1.8|1.0|0.6|-0.4<br>|
|92 - **95**|2.4|0.7|-1.6|0.0|1.5|1.5|18.9|27.7|8.8|3.0|**1.5**|-1.5|0.6|0.7|0.1|
|93-96|2.6|0.0|-2.6|0.6|0.0|-0.6|23.1|33.8|10.8|3.8|2.3|_-1.5_|0.0|0.8|0.8|
|94-97|3.3|1.0|-2.3|0.0|0.0|0.0|24.0|.35.4|11.4|3.3|3.1|-0.2|1.7|0.0|-1.7|
|Total'|2.1|0.6|-1.5|0.1|0.4|0.3|23.5|32.1|8.6|3.5|1.8|-1.7|0.6|0.9|0.3|
|_ENECE_**_992_**|21.0|||0.3|||18.8|||5.53|||0.5|||
|_ENECE 99, LS'_|17.2|||0.1|||30.5|||4.71|||0.1|||
|_ENECE 99, US'_|4.1|||0.2|||18.2|||2.29|||0.3|||

**1. Sample: Workers** in **the matching group.**

**2. Sample: All workers.**

**3. Sample: Workers with lower-secondary complete**<sup>**and 3 years of experience (18 and 19 years old).**</sup>

4. **Sample: Workers with upper-secondary complete**<sup>**and 1-5 years of experience (22-26 years old).**</sup>

**Table It. (cont.)**

|_Cohort_|_Commer_<br>_Control_<br>_Group_|_ce, Restau_<br>_Hotels_<br>_CONAL_<br>_EP_|_rants, and_<br>_Difference_|_Tra_<br>_Co_<br>_Control_<br>**_Group_**|_nsportatio_<br>_mmunica_<br>_CONAL_<br>_EP_|_n and_<br>_tions_<br>_Difference_<br>**__EP_**|**_Fin_**<br>_Control_<br>**_Group_**|**_ancial Ser_**<br><sup>_CONAL_</sup><br>_EP_|**_vices_**<br><sup>_Difference_</sup>|_Person_<br>_S_<br><sup>_Control_</sup><br>**_Group_**|_nel, Com_<br>_ocial Serv_<br><sup>_CONAL_</sup>|_mon, and_<br>_ices_<br><sup>_Difference_</sup>|
|---|---|---|---|---|---|---|---|---|---|---|---|---|
|90-93|<br>22.6|23.0|0.4|4.2|5.4|1.2|3.0|4.1|1.1|38.7|34.5|-4.2|
|91-94|28.4|25.6|-2.8|6.2|4.2|-2.0|2.1|2.4|0.3|32.5|29.8|-2.7|
|92 - 95|30.2|25.5|-4.6|7.1|2.2|-4.9|1.8|4.4|2.6|36.1|35.8|-0.3|
|93 - 96|28.8|20.8|-8.1|4.5|0.8|-3.7|0.0|3.1|3.1|36.5|38.5|1.9|
|94 - 97|27.3|21.9|_-5.4_|4.1|2.1|-2.0|1.7|0.0|-1.7|34.7|36.5|1.7|
|Total'|27.5|23.6|-3.9|5.3|3.1|-2.2|1.7|2.9|1.2|35.6|34.6|-1.0|
|_ENECE_**_992_**|21.5|||4.5|||0.9|||27.0|||
|_ENECE 99, LS'_|22.1|||2.1|||0.2|||22.9|||
|_ENECE 99, US'_|32.8|||8.8|||2.9|||30.5|||

1. **Sample: Workers** in **the matching group.**

**2. Sample: All workers.**

**3. Sample: Workers with lower-secondary complete and**<sup>**3 years of experience (18 and 19 years old).**</sup>

**4. Sample: Workers with upper-secondary complete and 1-5 years of experience (22-26 years**<sup>**old).**</sup>

33
Development at the border: policies and national integration in Cˆote d’Ivoire and its neighbors Denis Cogneau, Sandrine Mespl ́e-Somps and Gilles Spielvogel<sup>_∗_</sup> Keywords: National Integration, Africa, Borders, Economic Geography, Welfare. JEL classification codes: O12, R12, P52 Sector Board: EPOL

> _∗_ Denis Cogneau (corresponding author) is senior research fellow and associate professor at Paris School of Economics - IRD; his e-mail address is denis.cogneau@psemail.eu. Sandrine Mespl ́e-Somps is research fellow at Institut de Recherche pour le D ́eveloppement (IRD), UMR 225 DIAL, Universit ́e Paris Dauphine; her e-mail address is mesple@dial.prd.fr. Gilles Spielvogel is assistant professor at Universit ́e Paris 1 Panth ́eon-Sorbonne, UMR 201 “D ́eveloppement et Soci ́et ́es” (Universit ́e Paris 1 - IRD), and DIAL; his e-mail address is gilles.spielvogel@univparis1.fr. The authors thank the National Institutes for Statistics of Cˆote d’Ivoire, Ghana, Guinea, Mali, and also Burkina Faso, for giving access to their survey data. They thank Charlotte Gu ́enard and Constance Torelli for their participation in the first stage of this study; for historical archives, excellent research assistance from Marie Bourdaud and Ang ́elique Roblin is gratefully acknowledged. They last thank seminar participants at Oxford (CSAE), The Hague (ISS), Clermont-Ferrand (CERDI), Paris (CEPR/EUDN/AFD Conference and PSE), and Washington (World Bank), as well as three anonymous referees. The usual disclaimer applies. A supplemental appendix to this article is available at http://wber.oxfordjournals.org/.

1
subnational level.

Our route for investigating these issues is to begin in section 2 with a selective overview of the facts concerning the growth of new productive activities in developing countries. We then outline a framework of analysis that can be used to think about the determinants of structural change and growth, developing our 1<sup>st</sup> and 2<sup>nd</sup> advantage distinction (section 3). Section 4 goes into more detail, outlining what we know about some of the key elements of 1<sup>st</sup> and 2<sup>nd</sup> advantage based on the available evidence. Section 5 turns to work on India, as an illustration of how our approach can be used to generate insights into the microeconomic determinants of structural change. Section 6 concludes.

# **2.  Aspects of Modern Economic Growth**

Much of the recent work on the determinants of growth has focussed on country aggregate growth performance. The most popular examples of this are cross-country growth regressions, typically regressing growth performance on a number of explanatory variables. While these regressions reveal something of the importance of 1<sup>st</sup> advantages, such as human capital, good policy and institutions, and open trade regimes, many of the results are not particularly robust (see Djankov and others 2003; Rodrik 2003). Furthermore, they fail to capture some key aspects of modern economic growth. An aggregate approach overlooks two of the most important aspects of the performance of many developing countries: the uneven performance of different regions within each country, and the different performance across sectors.

# _Spatial Concentration_

For many countries development is associated with increasing spatial inequality. The finding of rising spatial inequality during development dates back at least to Williamson (1965) and has been confirmed in many studies since (e.g. the studies of urban concentration by Shishido 3
the same proxy for Capacity Agglomeration, Li et al. (2017) find that this measure helps explain China’s productivity advantage over India in a quantitatively important way, while Clarke et al. (2015) find that it has predictive power for firm-level job growth using WBES data similar to that on which we rely.

# **3. Baseline Results**

We present our baseline results for both the growth of employment (Lgrowth) and the growth of labor productivity (LPgrowth) in Table 3. As can be seen, the firm level controls tend to perform as we might expect _a priori_ . To begin with, foreign ownership is strongly associated with better firm performance. Based on the estimate, a one standard deviation (SD) increase in the share of foreign ownership (0.25) is associated with increases in Lgrowth and LPgrowth of 0.5 percentage points and 1.3 percentage points, respectively. In addition, firms whose ownership is more dominated by a single owner (as reflected in a higher ownership share for the largest shareholder) suffer from both lower Lgrowth and LPgrowth. This likely reflects the effect of family ownership of firms, which tends to result in a lower quality of management, and perhaps worse aspects in other areas as well, such as lower levels of investment in the human capital of employees. A oneSD increase in family ownership is associated with reductions of 0.3 and 0.7 percentage points in Lgrowth and LPgrowth, respectively.

Relative to firms with the smallest initial size (i.e., employing 20 or fewer workers), those firms that initially employ 20-100 workers have higher Lgrowth (by 2.6 percentage points) and LPgrowth (by 3.6 percentage points). Those employing more than 100 workers grow even faster: Lgrowth by 8.7 percentage points and LPgrowth by 4.6 percentage points. Consistent with the literature (Ayyagari et al., 2011), older firms experience slower Lgrowth as reflected by the negative coefficient on the variables Age 6-10 and Age 10+. However, accompanying this, older firms do experience faster LPgrowth.

Turning to the main variables of interest, the critical importance of Basic Protection is evident. First, Corruption Obstacle proves to be damaging for employment, but not LP, growth. A one SD increase in this variable is associated with a drop in Lgrowth of 0.4 percentage points. By contrast, it has no significant impact on LPgrowth. The negative estimated impact on Lgrowth is consistent with Freund et al.’s (2016) finding that heightened corruption promotes increased management harassment, which should contribute to lower firm growth. Second, a lack of basic 13
gain in the sense that real GDP exceeds real je GDPjo , whereas other countries – with low export e o prices or high import prices – will have real GDP less than real j GDPj .

Second, in order for export prices to influence the measurement of real GDPjo , countries need to produce some goods in common. To see this, consider the opposite case where all countries are fully specialized in their own goods. Then the summations used in (13) to obtain reference prices for the export goods would actually be over a _single_ country, i.e. the unique country exporting that good. For convenience, suppose that each country exports just one good, x x o and re-order goods so that xij = 0 for i ≠ j and xjj > 0, so (13) becomes π j = p jj / PPPj . It follows from (19) that PPP =jx PPPjo , so with complete specialization, the PPP for exports is identical to the overall output PPP. This means that export prices will not contribute to any differences between real GDP and real je GDPjo ; only import prices matter. Countries with high import prices will still have real GDP less than real je GDPjo , due to their poor terms of trade.<sup>10</sup>

# **4. Application to UN Trade Data and Penn World Tables**

In this section we apply our formulas to a dataset for expenditure and trade in 1996 for a set of 151 countries. The source for the trade data in the NBER-UN dataset described in Feenstra _et al_ (2005), and we use only data for those countries that also appear in the PWT.<sup>11</sup> This database contains specific product data classified at the 4-digit SITC level, from which we obtain unit-values for exports and imports. The number of unit-values on the export side ranges from 10 for Chad to 1,020 in the United States, and on the import side from 29 in Israel to 776 in Egypt.

It is well-known that trade unit-values are measured with error, and so we applied a regression-based procedure to omit outliers. The procedure was to predict import and export unit values based on tariff rates, distance to trading partners and exporter wages.<sup>12</sup> Unit values which were greater than five or less than one-fifth times the predicted unit value were identified and

> 10 However, in a two-good, two-country Ricardian model, a unique country imports each good. Say country j export m m o m o good j and import good i ≠ j. Then (14) becomes π j = p ij / PPPj , for i =1,2, so that PPPj = PPPj from (19). Since x o e o e o PPPj = PPPj also, it follows by comparing (8)-(10) with (12)-(15) that PPPj = PPPj and so real GDPj = real GDPj . Thus,  the two concepts of real GDP do not differ in this case. We thank a referee for alerting us to explore it. 11 The only country excluded is Nigeria, because it resulted in some negative reference prices.

14
# **2.  The Design of the Experiment**

Household surveys vary across multiple dimensions. The decisions on content, respondent, interviewers, timing and the like are driven by a combination of data needs, cost considerations, assessments of each household member’s knowledge and willingness to respond and sampling strategies. There are tradeoffs involved: greater detail in questions may aid recall but this boost to data quality and comprehensiveness can be counteracted by respondent fatigue arising from interview length. High field costs can be minimized by using proxy respondents but this may decrease data quality and, thus, may not actually represent cost savings at all. To provide some insights into the tradeoffs involved in the area of collection financial data in household surveys, we developed an experiment to test whether reported use of financial services is affected by either the choice of respondent or the format in which questions on financial services are posed.

Respondents selected to provide financial service use data in surveys are very often the head of household (however defined). This person is asked to provide information on household use of loans and savings and, more rarely, insurance. This is the way that Living Standards Measurement Study (LSMS) surveys were typically carried out. However, there are concerns that not all individual financial service use in the household is known to the head of household and thus, the data collected in this manner may understate overall use of services and, perhaps underestimate specific types of services or use by certain categories of household members. Reviews of both savings and credit issues in LSMS surveys recommended the alternative method of using direct informants to collect savings and credit behavior (Kochar, 2000; Scott, 2000). In this way, data are collected from all adults in the household about their own use. Several 9
Officials are slightly more supportive of accommodations for disabled students (54 percent of EAP officials strongly support accommodation versus 48 percent in non-EAP countries). However, there is some variation; in Vietnam and Lao PDR, more than 15 percent of officials do not agree that accommodations should be made so that children with disabilities can be welcomed in schools, versus 4 percent on average in non-EAP countries (Figure 2b).<sup>9</sup> We note that inclusion in “regular classrooms” as posed in the question is not always beneficial for the student with disabilities, especially if the accommodations and support available in the school are inadequate to their particular needs.

_Figure 7: Share of officials agreeing with statements on access to disabled children._ a. “Children with disabilities deserve the same level of access to public schooling as children without disabilities.” <!-- Start of picture text --> 100%<br>80%<br>60%<br>40%<br>20%<br>0%<br>IDN LAO MNG PHL VNM Non-EAP<br>Strongly agrees Agrees<br>Disagrees Strongly disagrees<br>Does not know<br><!-- End of picture text --> b. “In most cases, accommodations should be made so that children with disabilities can be included in regular classrooms with children who do not have disabilities.” <!-- Start of picture text --> 100%<br>80%<br>60%<br>40%<br>20%<br>0%<br>IDN LAO MNG PHL VNM Non-EAP<br>Strongly agrees Agrees<br>Disagrees Does not know<br><!-- End of picture text --> Source: Calculations from CDG–World Bank 2022 microdata.

There is larger diversity in responses across countries regarding gender equality. In Vietnam, Mongolia and Lao PDR, more officials disagree with equalitarian statements (Figure 8a). Surveyed EAP officials on average support gender equity more strongly than officials from other regions. Surveyed officials from EAP are also much less likely to believe that girls face barriers to education in their countries (Figure 8b); this aligns with higher levels of female achievement than males in all subjects on the 2019 SEA-PLM, as can be seen in Table 2 (in the Annex). We find no correlation between the share of respondents agreeing to the three first statements and per capita GDP. There is however a small significant correlation between per capita GDP and the share of officials disagreeing with the fact that girls face additional challenges in accessing and completing their education. However, this correlation disappears once one takes into account the region: EAP countries appear as a group very different from the rest of the sample.

> 9 We speculate that officials in Vietnam and Lao PDR  may view inclusion as a burden, especially if student-teacher ratios are high and supports for special education are not available. More knowledge and awareness of options to make inclusion possible may be helpful in these country contexts.

11
# so

in absolute terms from the universal targeting scheme. Table 10 shows that under this scenario, the head-count ratio increases from 8.7 percent to a dramatic 69.9 percent for government households, and increases from 1.8 percent to 67 percent for the formal households.<sup>43</sup> For all the other households the poverty index falls. At the national level, the universal transfer program when applied to all households reduces total poverty by 7 percentage points from 37 percent to 30.1 percent. In the traditional calculations, this would have led to a total eradication of poverty.

The results obtained under the "ALL" scenario are driven by the financing scheme imposed. Since the program is self-financed with a neutral effect on the real government budget, the high-income households will pay more than what they receive. At the same time, the results are affected by the inter-household transfers since poor household groups that receive transfers from the high income households would bear part of the tax burden so that the poverty reduction is less than anticipated." The individual scenarios produce a different pattern. Looking at the figures in Table 10, we see that even when the transfer scheme is applied to each group individually, total poverty for the group is not eliminated. For example, when the MEXP is targeted, poverty for this group is reduced by 76 percent, but there is still a core poverty level of 10 percent of total population in the export sector. The same is true for the other households. The head-count ratio resulting from these 43 World Bank (1990) provides similar results for Malawi. An income transfer program has a significant impact on the poor at the expense of the non-poor. The resultq do not take into account general equilibrium effects.

I Our simulation results also indicated that the leakage effect will be smaller when the feature of inter-household transfer is taken out from the model.
# **4.2 Robustness Checks**

The next step is to check the robustness of these findings to alternative specifications and data sources. Table 8, in the annex, reproduces the baseline results using ICAC data for yields and production, instead of FAO data. All the parameters of interest are of similar signs and magnitude. More importantly, we now turn to discussing potential serial correlation, reverse causality and endogeneity.

Bertrand _et al._ (2004) showed that serial correlation causes difference-in-difference standard errors to understate the standard deviation of the estimated treatment effects thus leading to overestimation of _t_ -statistics and significance levels. To check that our results do not suffer from such bias, we follow their strategy of “ignoring time series information”. We start by regressing log ( _Yit_ ) on country and year fixed effects as well as our additional vectors of covariates ( _C_ ). We then obtain the effect of the market structure variables and their standard errors from a second OLS regression on the residuals, which now form a two-period panel (with pre-reform being characterized by _Monopoly_ , the default category, and post-reform corresponding to either _Post Reform_ or _Regulation_ , _Low competition_ and _Strong competition_ ). We estimate the two following equations: _Log(Yit) = β0 +β1 Cit + γt + ci + εit (2)_ _Residuals it_ = _β0 + β1 Iit + εit_ where _Residuals_ are the residuals from equation (2). The results of the second regressions are displayed in Tables 4 (yield) and 5 (production). Both the significance and the signs of the institutional variables (the post-reform variable as well the disaggregated market structure indices) are very much in line with those found with the baseline specification. Two differences, however, are worth noting. First, whereas yields are still found to be higher in liberalized markets of ESA and non-Francophone WCA, this effect is of lower magnitude and it is not significant anymore in moderately competitive markets. Second, whereas production is still found to be higher in liberalized markets of Francophone WCA, the effect is a bit lower. More interesting is the fact that production is found to be significantly lower in strongly competitive markets in ESA and non-Francophone Africa. This suggests that in strongly competitive markets, the production reduction induced by market exit has exceeded the price and productivity-induced production boost among the most efficient farmers. This finding is consistent with the finding by Delpeuch _et al._ (2010), that input distribution on credit – and hence participation in cotton cultivation on a large scale – is likely to be more compromised, the higher the degree of competition.

17