rafmacalaba/datause-encoder-data huggingface dataset:
The data shows that deindustrialization has permeated Central America. Except for Panama, the industrial employment shares have contracted in each regional economy, with an average decline of 2.5 percentage points (pp). In the first step of my study, I uncover the fundamental drivers of industrial change in each country. Specifically, I use the sectoral data on employment, value-added, consumption, and trade to identify the importance of three channels in accounting for the dynamics. First, a decline in the industrial labor allocation can be demand-driven, i.e., due to a fall in the industrial share of final consumption. Second, a rise in industrial imports substituting domestic production may lead to trade-induced deindustrialization. Finally, an intensification in the barriers, or labor market _wedges_ (Hsieh & Klenow, 2009), to the movement of resources into the industry can have the same qualitative effect on labor allocation.

The accounting reveals that shifts in labor market wedges are essential in explaining the region's deindustrialization. The channel causes industrial employment to contract in each regional economy. Its impact on industrial share varies across countries, ranging from a more than 5pp decline in Panama and El Salvador to less than one pp decay in Costa Rica. These wedge-driven contractions are higher than the actual share loss in three of the five economies that have experienced deindustrialization. The channel plays a secondary role in Costa Rica, explaining only 15 percent of the country's massive 6.2 pp drop in industrial share.

Global trade has flourished over the last two decades. Trade, therefore, can potentially explain deindustrialization in countries having a comparative advantage in non-industrial sectors. Instead of engaging in production to satisfy their industrial demand, it might be economical for these economies to import these goods. Surprisingly, I do not find evidence supporting this oft-cited trade-led deindustrialization hypothesis for Central America. Instead of creating headwinds, trade has usually fostered industrial expansion in the region. Nicaragua and El Salvador are the two economies where the channel has induced deindustrialization. Still, its actual impact is benign in both cases.

Finally, changes in final consumption had a varied effect across the region. This channel aided industrialization in four economies, but an allocation of final consumption away from industrial goods led to a labor reallocation away from the sector in Costa Rica and Honduras. Quantitatively, this is the dominant factor that accounts for the deindustrialization in the two countries.

The second part of the paper aims to quantify the aggregate impact of rising wedges. Their presence restricts the efficient flow of resources across sectors and may keep labor trapped in non-industrial 3
such constraints may provide us with more realistic benchmarks against which to judge distributional outcomes.

Assessing incidence and determining how best to improve distributional outcomes are the vital first steps. But, the follow-up-reform implementation-begs a further understanding of the political economy of reform: Why and when is reform undertaken? Why and when is it successful? Economists are often at a loss when such issues come to the fore, but they should make no mistake about their relevance.

# _3.2 Results_

Provided one is aware of their deficiencies, much of the data and methods commonly used in practice can be useful and informative. The (few) studies that have attempted to compare results on incidence have found the methodologies broadly in agreement (Selden and Wasylenko discuss this issue in PSP). Still, the results should be taken as indicative of likely directions of benefit incidence, rather than precise magnitudes. Subject to the caveats discussed above, some reasonably clear patterns can be discerned from studies of the distribution of benefits from public spending in developing countries. They are briefly summarized here.<sup>6</sup>

## 3.2.1 Lessons from benefit incidence studies

Only a few benefit incidence studies have examined the totality of public spending (Selden and Wasylenko 1992, provide a review). Studies more commonly focus on one or two sectors as do the case studies in this book. I will follow suit here.

A distinction should always be made between the distribution of benefits in monetary amounts and that of benefits expressed as a percentage of the welfare indicator (typically per capita consumption or income). Investigations of the education, health, social transfers and nutrition sectors 22
22 26. In addition to the expected effects of FPHH on TFR and REXNP on IMR, the reduced form gives the extent of cross effects linking family planning with infant mortality reduction and non hos?ital health expenditures with reduced fertility. The reduced form coefficient of FPHH on IMR reveals<sup>that</sup> the reduction in infant mortality with a doubling in family planning is almost 16%. Correspondingly, the reduction in fertility with a doubling in non hospital health expenditures is 25%.

Table-3

# moRTALITY-FERTILITY RESPONSE ELASTICITIES A/

||TFR||
|---|---|---|
|ILLIT|.00|.13|
|LYP|.42|.26|
|PURB|-.26|-.16|
|TOIL|-.04|-.25|
|CAL|-.02|-.15|
|REXNP|-.04|-.25|
|REXFPP|-.25|-.16|

A/Based on reduced form coefficients for alternative #2

# V. Policy Implications of Mortality-Fertility Interaction

27. The interaction of infant mortality and fertility is usually ignored in appraising the effectiveness of family planning and MCH programs, but tLhe illustration for Indonesia shows that this interaction can greatly affect the response of fertility and mortality and should be considered in
Figure 3. Evolution of speech content in Chile <!-- Start of picture text --> 100%<br>Rest of the topics<br>Copper<br>Social policy<br>75%<br>50%<br>Education and<br>Infrastructure<br>health<br>25%<br>Public Social<br>administration development<br>0%<br>1941 1945 1955 1965 1973 1982 1986 1990 1994 1998 2002 2006 2010 2014<br>Topic proportion<br><!-- End of picture text --> Note: This Figure shows the topic probabilities estimated with LDA. The topic probabilities can be thought of as representing the proportion of each document that belongs to each topic. Only topics whose average document probability exceeds 10% in at least one decade are presented, the rest are grouped as a residual.

Figure 4. Evolution of speech content in the República Bolivariana de Venezuela <!-- Start of picture text --> 100%<br>Rest of the topics<br>Social Oil industry<br>policy<br>75%<br>Chavismo<br>50%<br>Infrastructure<br>25% Public<br>administration<br>Social<br>development<br>0%<br>1940 1943 1947 1955 1959 1962 1966 1976 1984 1994 1998 2001 2004 2007 2010 2014<br>Topic proportion<br><!-- End of picture text --> Note: This Figure shows the topic probabilities estimated with LDA. The topic probabilities can be thought of as representing the proportion of each document that belongs to each topic. Only topics whose average document probability exceeds 10% in at least one decade are presented, the rest are grouped as a residual.

12
23 Table 3: Robustness regressions for the difference in bank lending between 2006 and 2009, with alternative measures<sup>_†_</sup>

||**C1**|**C2**|**C3**|**C4**|**C5**|**C6**|**C7**|**C8**|
|---|---|---|---|---|---|---|---|---|
||_LtA_<sup>a</sup>|_LtA_<sup>a</sup>|_LtA_<sup>a</sup>|_LtA_<sup>a</sup>|_Loans_<sup>b</sup>|_Loans_<sup>b</sup>|_LtA_<sup>a</sup>|_LtA_<sup>a</sup>|
|Financial reforms|-0.727<br>(0.22)***|-0.758<br>(0.30)**|-0.611<br>(0.23)***|-1.081<br>(0.36)***|||||
|Crises experience|||-0.087<br>(0.04)**|-0.136<br>(0.05)***|-6.485<br>(2.53)**|-6.111<br>(2.86)**|-0.092<br>(0.05)**|-0.085<br>(0.04)**|
|||||_Bank c_|_ovariates_||||
|Size|-0.000|-0.000|0.000|0.000|0.185|0.186||0.000|
||(0.00)|(0.00)|(0.00)|(0.00)|(0.05)***|(0.05)***||(0.00)|
|Solvency|-0.166|-0.165|-0.156|-0.133|-3.126|-3.833||-0.167|
||(0.09)*|(0.09)*|(0.09)*|(0.09)|(2.32)|(2.59)||(0.08)**|
|Proftability|-0.007|-0.007|-0.016|-0.020|0.406|0.178||-0.018|
||(0.01)|(0.02)|(0.02)|(0.02)|(1.55)|(1.56)||(0.02)|
|Interest margin|0.447|0.488|0.646|0.707|50.148|53.677||0.628|
||(0.18)**|(0.19)**|(0.19)***|(0.19)***|(15.15)***|(15.70)***||(0.20)***|
|||||_Host count_|_ry covariates_||||
|GDP per cap.||0.000||0.000||0.005|||
|||(0.00)||(0.00)||(0.01)|||
|Lagged GDP growth||-0.110||-0.611||-58.864|||
|||(0.33)||(0.54)||(35.84)|||
|Current account balance||-0.011||-0.194||4.487|||
|||(0.11)||(0.14)||(8.52)|||
|Infation||-0.119||0.692||25.517|||
|||(0.53)||(0.34)**||(39.43)|||
|∆GDP|||||||-0.001|-0.001|
||||||||(0.00)|(0.00)|
|∆GDP|||||||0.056|0.032|
||||||||(0.32)|(0.32)|
|∆Current|||||||0.175|0.078|
||||||||(0.31)|(0.32)|
|∆Infation|||||||0.530|0.428|
||||||||(0.48)|(0.47)|
|Host FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|1st-stage _F_|||0.00|0.00|0.00|0.00|0.00|0.00|
|Underid. test|||0.00|0.00|0.00|0.00|0.00|0.00|
|Weak id. test (rel. bias)|||_<_5%|_<_5%|_<_5%|_<_5%|_<_ 5 %|_<_5%|
|Overid. test|||0.66|0.68|0.64|0.66|0.82|0.80|
|_R_<sup>2</sup>|0.06|0.06|||||||
|2nd-stage _F_|0.00|0.00|0.00|0.00|0.00|0.00|0.09|0.01|
|Estimation|OLS|OLS|IV|IV|IV|IV|IV|IV|
|Obs. (host countries)|397 (80)|391 (80)|340(59)|340(59)|347 (61)|346 (61)|349 (62)|346 (61)|

> _†_ All changes in home-country variables are for 2006 and 2009, with the exception of GDP growth, which is growth rate between 2005 and 2010. Heteroskedasticity and host country correlation-robust standard errors are reported in parentheses. A constant term was included in the regressions, but not reported. The underidentification test is the Kleibergen-Paap rk _LM_ , the weak identification test is the Kleibergen-Paap rk Wald _F_ , and the overidentification test is the Hansen _J_ .<sup>_∗_</sup> indicates significance at 10 percent level,<sup>_∗∗_</sup> indicates significance at 5 percent level, and<sup>_∗∗∗_</sup> indicates significance at 1 percent level.

> * The dependent variable is the difference in bank loan-to-asset (LtA) ratio between 2006 and 2009.

> _‡_ The dependent variable is the difference in bank gross loans between 2006 and 2009.
# **Table 11.  Sector Import Intensities by Regional Market: Regional Imports of the Sector as a Percent of Regional Consumption of the Product**

|Good|Central Fa|r East|North|Siberia|South|Urals|Moscow|St.<br>Petersb.|Tumen|North-<br>west|
|---|---|---|---|---|---|---|---|---|---|---|
|AGR|4|4|4|4|4|4|4|4|4|4|
|AIR|3|3|3|3|3|3|3|3|3|3|
|CHM|35|36|30|47|29|33|74|58|19|57|
|CNM|13|16|13|18|10|11|29|25|8|20|
|COL|7|7|7|7|7|7|7|7|7|7|
|CON|8|8|8|8|8|8|8|8|8|8|
|CRU|5|5|5|5|5|5|5|5|5|5|
|ELE|1|1|1|1|1|1|1|1|1|1|
|FIN|1|1|1|1|1|1|1|1|1|1|
|FME|32|17|19|14|36|17|38|37|25|75|
|FOO|25|23|13|15|20|15|31|94|10|50|
|GAS|2|2|2|2|2|2|2|2|2|2|
|HEA|1|1|1|1|1|1|1|1|1|1|
|HOU|8|8|8|8|8|8|8|8|8|8|
|MWO|36|37|24|15|27|26|98|100|16|53|
|NFM|16|40|41|96|35|23|39|41|23|25|
|OIL|8|8|8|8|8|8|8|8|8|8|
|OTH|19|19|19|19|19|19|19|19|19|19|
|OTI|7|6|6|6|6|6|7|7|6|6|
|PST|2|2|2|2|2|2|2|2|2|2|
|RLW|0|0|0|0|0|0|0|0|1|0|
|SCI|0|0|0|0|0|0|0|0|0|0|
|TMS|6|6|6|6|6|6|6|6|6|6|
|TPP|13|11|28|4|19|5|60|83|1|78|
|TRD|0|0|0|0|0|0|0|0|0|0|
|TRK|2|2|2|2|2|2|2|2|2|2|
|TRO|1|1|1|1|1|1|1|1|1|1|
|CLI|73|73|73|73|73|73|73|73|73|73|
|Total|142|52|35|142|140|268|528|140|81|41|

See Tables 1 and 2 for sector and region definitions. Source: Roskomstat unpublished surveys and authors' calculations.

47
22 Consequently, the country was unable to produce the goods at a cost advantage and therefore unable to compete in these industries.

**Table** **<u>3. The Economics of Unrealistic Ambitions</u>**

|**Country**|**Industry**|**Time**|**Main producer**<br>**at Time**|**Real GDP pc**<br>**Latecomer**<br>**Country**|**Real GDP pc**<br>**Leading**<br>**Country**|**Income Ratio**<br>**Follower versus**<br>**Leader**|
|---|---|---|---|---|---|---|
|China|Automobile|1950s|USA|577|10,897|5%|
|DRC|Automobile|1970s|USA|761|16,284|5%|
|Egypt|Iron,Steel,Chemicals|1950s|USA|885|10,897|8%|
|India|Automobile|1950s|USA|676|10,897|6%|
|Indonesia|Ships|1960s|Netherlands|983|9,798|10%|
|Senegal|Trucks|1960s|USA|1,511|13,419|11%|
|Turkey|Automobile|1950s|USA|2,093|10,897|19%|
|Zambia|Automobile|1970s|USA|1,041|16,284|6%|

Source: Author's calculations based on data from Maddison (1995).

To implement the comparative-advantage-defying strategy, developing country governments had to protect numerous nonviable enterprises in the priority sectors. Administrative measures to which governments resorted to reduce the investment and operation costs of nonviable enterprises included granting those enterprises a market monopoly, suppressing interest rates, overvaluing domestic currency, and controlling prices for raw materials. Such interventions caused widespread shortages in funds, foreign exchange, and raw materials. Consequently, governments also had to allocate resources directly to these enterprises through administrative channels, including national planning in the socialist countries and credit rationing and investment and entry licensing in nonsocialist developing countries. For ease of implementation, many countries also relied on state-owned enterprises to develop the targeted industries.

Protection also led to other types of costs. Prices of imports and of import-substituting goods increased relative to the world price, pushing the economy to consume the wrong mix of goods from the point of view of economic efficiency. Markets fragmented as the economy produced too many small-scale goods, again resulting in loss of efficiency. Protectionism also lessened competition from foreign firms and encouraged monopoly power among domestic firms whose owners were politically well connected. Moreover, it created opportunities for rents and corruption, which raised input and transaction costs.

In some cases (mainly in Eastern European and other socialist countries of the former Soviet Union) the industrial development brought about by the comparative-advantage-defying strategy appeared to be successful at the beginning because large-scale investment through massive state mobilization of resources increased the growth rate and improved productivity indicators. But firms in the capital-intensive sectors depended for their survival on the government‘s subsidies and protection, and when the state could no longer mobilize resources for further investment, the economy became stagnant. Moreover, the investment in the capital-intensive sectors generated little employment. The labor force remained mostly in the rural sector.
<!-- Start of picture text --> 1<br><!-- End of picture text --> CONS 0 0 CONS 04 ~~M2 90-S~~ <u>4 By</u> 0 0 CONS < CATA ~~—————— <—~~ = S<B INC 0—S+By 0 M cons < CATA,yc for sure when S < 0 (e.g. the income endowment is point ein Figure 2) or when S = 0 (i.e. the income endowment is point a). We also have CATAcgons < iwc When0 < S < By(i.e. the income endowment lies between points aand d), and we have cons = CATA;ycwhen S = By > 0 (i.e. the income endowment is point d). We only have cons > CATA;yc when S > By > 0 (i.e. the income endowment lies to the southeast of<sup>point</sup> d, e.g. point g). Thus, when the individual is a borrower after a health shock, the income-based ratio
We find that increases in equity inflows into emerging markets are associated with higher values of country-level equity issuance proceeds. This indicates that inflows imply more than a simple transfer of equity ownership from domestic to foreign investors. Using firmlevel data, we show that large firms disproportionately drive this relation. Instrumenting equity inflows (both contemporaneous and lagged) with various alternative measures that capture the exogenous variation in other countries’ attractiveness to foreign investors, we show that our results are driven by variation in foreign equity capital supply.

Lastly, we find that equity capital inflows lead large firms to increase corporate investment. We also show that large firms invest, on average, a substantial fraction of the funds raised in equity offerings. Our evidence is consistent with capital inflows lowering equity financing costs, which allows firms to raise funds to finance new investments. More generally, our results indicate capital inflows affect real economic activity through equity issuance activity, among other possible channels.

Our work shows how micro data can provide unique insights into how subsets of firms drive aggregate relations. Our findings suggest that the issuance and investment behavior of large firms in emerging markets is highly responsive to equity inflows. But apparently, many other emerging market firms are not the target of global market investors’ share purchases. For those smaller firms, large flows of funds connecting their countries to global markets have little direct effect on their propensity to issue equity. This suggests that it can be useful to divide firms in emerging economies into two categories: those for which equity capital inflows have significant and important direct effects on the cost of issuing capital, and those for which they have little effect.

To the extent that equity inflows lower the cost of finance for large firms, that may create a competitive advantage for those firms. At the same time, it is possible that large firms 30
findings from earlier survey rounds where he concludes that the returns to education of the household head in urban areas rose over time while they fell in rural areas.

For both rural and the urban households, the effects of changes in returns to occupations dominate that of changes in occupational characteristics. For rural households, the increases in returns to agricultural labor and farming are substantial and consistent with poverty reduction seen among households headed by an agricultural day laborer or farmer (see Table 3). This is consistent with Wodon’s results from 1991-1996 where returns to agricultural occupations rose following a decline in the 1980s. For urban households, returns to non-agricultural daily labor and self-employment improved significantly, suggesting that rising labor incomes and increased earnings from nonfarm self-employment in urban areas contributed to reducing poverty.

Among urban households, the coefficients on remittances (domestic and foreign) increased sharply from 2000 to 2005, suggesting that a rise in ‘returns’ to remittances contributed significantly to urban consumption growth. Among rural households, both increase in remittances and returns to remittances had small contributions to consumption growth. These impacts are consistent with the findings of a recent study on the effect of remittances on household welfare in Bangladesh (Sharma and Zaman, 2009).

Given the role played by location effects in explaining household consumption (see Section III), time trends of these effects help understand whether and how the pattern of regional disparities has changed over the years, and how these changes may have contributed to reduction in national poverty. The results illustrate how spatial dimensions of poverty have shifted in Bangladesh. First it is clear that there has been some reduction 18
**Table 1.1. Domestic savings and infrastructure investment needs**

As of 2006

||Gross domestic savings<br>(US$ millions)<br>Estimated infrastructure<br>investment needs (US$ millions)|Difference between<br>gross domestic savings and<br>infrastructure investment needs<br>(US$ millions)|
|---|---|---|
|South Africa|41,200<br>25,406|15,794|
|Nigeria|38,400<br>11,940|26,460|
|Sudan|5,310<br>3,719|1,591|
|Kenya|1,710<br>2,340|–630|
|Cameroon|3,160<br>1,866|1,294|
|Côte d’Ivoire|4,820<br>1,722|3,098|
|Ethiopia|–813<br>1,327|–2,140|
|Tanzania|1,540<br>1,321|219|
|Ghana|1,000<br>1,119|–119|
|Zambia|1,970<br>1,044|926|
|Uganda|738<br>912|–174|
|Senegal|790<br>831|–41|
|Mozambique|1,540<br>761|779|
|Congo, Dem. Rep.|398<br>815|–417|
|Namibia|2,180<br>640|1,540|
|Chad|2,750<br>600|2,150|
|Burkina Faso|565<br>565|–1|
|Madagascar|748<br>545|203|
|Benin|298<br>520|–222|
|Niger|317<br>355|–38|
|Malawi|–189<br>221|–410|
|Rwanda|40<br>246|–206|
|Lesotho|–103<br>167|–271|
|Cape Verde|–25<br>92|–116|
|Chile|36,700<br>13,580|23,120|
|Malaysia<br>Sources: World Bank staff esti|62,300<br>14,876<br>mates based on GEM and WDI databases.|47,424|

The savings rate is an important macroeconomic indicator of an economy’s ability to generate funds for infrastructure. Extremely low income levels continue to keep access to basic savings instruments beyond the reach of most people in Sub-Saharan Africa, however. Savings rates in the region are by far the lowest worldwide—below 5 percent in several of the focus countries (Cape Verde, Ethiopia, Lesotho, Malawi, and Rwanda)—unsurprisingly, five of the six same economies that have a large shortfall in gross domestic savings vis-à-vis infrastructure investment needs. Several economies constitute notable 4
# _Dealing with Endogeneity_

Next, we address the endogeneity problems in the OLS regressions. First, it is likely that countries that grow faster engage in more trade than others. Faster economic growth may lead to technological and production developments that expand export markets while domestic demand for imports may grow with rising incomes. This will lead us to over-estimate the effect of both trade and the interactive term on growth (in the sense that the coefficient on the trade-regulation interactive term is expected to be negative but its absolute magnitude is likely to be biased downward). There may also be omitted variables that are correlated both with per capita incomes and trade that will bias the coefficients on trade such as for instance factors like infrastructure or governance. Following Frankel and Romer (1999), we use the fitted values of trade predicted by the exogenous variables in a gravity model as an instrument for trade.<sup>11</sup> Second, we instrument for the regulation index. Countries with rising or high incomes are more likely to face better regulatory environments. As countries grow faster, the costs of a heavy regulatory burden in the face of expanding markets and business opportunities becomes higher, thereby accelerating regulatory reform. The government may face greater pressures from the private sector to remove administrative constraints. We instrument for the regulation index with the share of population speaking English or a major European language as well as legal origin of countries. The premise is that colonial origin may have influenced the current regulatory state of countries by influencing their earlier institutional heritage. Legal origin may

> 11 We use Frankel and Rommer’s approach to get fitted bilateral trade shares (sum of imports and exports to GDP) for countries using 2000 bilateral trade data and we then aggregate the bilateral trade shares for each country i across its trade partners j. We use as instruments for bilateral trade shares geographical variables such as a dummy for landlocked countries, distance from equator, and other variables such as a dummy for a common border, language variables, population and cross-terms. See Frankel and Rommer (1999). In the case where we use trade/GDP at PPP (all in 1996 dollars) as the measure of openness, we also use as bilateral trade data sum of exports and imports to GDP at PPP (all in 1996 dollars).

15