rafmacalaba/datause-encoder-data huggingface dataset:
Table 11. Main features of global expansions (by region)

|||Global|expansion|s||Global|expansions|(excluding|initial ye|ars)|All|
|---|---|---|---|---|---|---|---|---|---|---|---|
|**East Asia and Pacific**|1976-81 19|83-90 19|92-2008 2|010-19 A|verage|1977-81 1|984-90 19|93-2008 2|011-19 A|verage|years|
|Output|6.8|8.0|8.7|7.1|7.6|7.5|8.0|8.5|6.8|7.7|7.0|
|Output per capita|5.0|6.0|7.6|6.3|6.2|5.7|6.1|7.5|6.1|6.3|5.4|
|Industrial production|...|12.7|10.4|8.0|10.4|...|12.7|10.4|7.3|10.1|9.9|
|Trade|10.2|10.1|12.5|7.2|10.0|11.7|10.4|12.2|6.0|10.1|8.6|
|Output (PPP)|6.8|7.7|8.3|7.0|7.5|7.4|7.8|8.2|6.7|7.6|6.9|
|Output per capita (PPP)|5.0|5.8|7.3|6.3|6.1|5.7|5.8|7.2|6.0|6.2|5.3|
|**Europe and Central As**|**ia**|||||||||||
|Output|2.8|1.9|2.2|3.2|2.5|2.1|1.6|2.9|3.0|2.4|3.2|
|Output per capita|1.9|1.1|2.1|2.7|1.9|1.2|0.8|2.8|2.5|1.8|2.6|
|Industrial production|...|...|3.5|4.2|3.9|...|...|3.9|3.6|3.7|3.3|
|Trade|4.5|1.0|6.2|5.0|4.2|4.3|1.0|8.0|4.2|4.4|5.0|
|Output (PPP)|2.8|1.9|2.1|3.0|2.4|2.1|1.5|2.8|2.9|2.3|3.2|
|Output per capita (PPP)|1.9|1.1|2.0|2.6|1.9|1.2|0.7|2.7|2.5|1.8|2.6|
|**Latin America and the**|**Caribbean**|||||||||||
|Output|4.9|2.0|3.2|2.2|3.1|4.7|2.6|3.3|1.7|3.1|3.9|
|Output per capita|2.5|-0.1|1.7|1.1|1.3|2.3|0.6|1.8|0.6|1.3|1.8|
|Industrial production|...|...|3.0|0.5|1.7|...|...|3.1|-0.4|1.4|1.7|
|Trade|7.5|4.6|7.2|4.6|6.0|8.6|6.1|6.9|3.2|6.2|5.5|
|Output (PPP)|4.8|1.9|3.2|2.4|3.1|4.7|2.5|3.3|1.9|3.1|3.8|
|Output per capita (PPP)|2.4|-0.2|1.7|1.2|1.3|2.3|0.4|1.8|0.8|1.3|1.8|
|**Middle East and North**|**Africa**|||||||||||
|Output|4.5|1.8|4.1|3.0|3.3|2.3|2.3|4.0|2.8|2.8|5.0|
|Output per capita|1.4|-1.3|2.2|0.9|0.8|-0.8|-0.8|2.1|0.7|0.3|2.4|
|Industrial production|...|...|...|...|...|...|...|...|...|...|...|
|Trade|0.7|0.0|5.4|3.0|2.3|-0.4|0.6|5.3|3.2|2.2|5.1|
|Output (PPP)|4.1|2.0|4.0|2.6|3.2|1.8|2.3|3.9|2.5|2.6|4.9|
|Output per capita (PPP)|1.0|-1.1|2.1|0.7|0.7|-1.3|-0.7|2.1|0.5|0.1|2.4|
|**South Asia**||||||||||||
|Output|4.1|5.6|6.1|6.8|5.7|4.5|5.4|6.2|6.5|5.6|5.0|
|Output per capita|1.6|3.1|4.2|5.5|3.6|2.0|3.0|4.2|5.2|3.6|3.0|
|Industrial production|...|...|...|...|...|...|...|...|...|...|...|
|Trade|7.2|5.1|13.0|6.9|8.0|7.0|4.5|12.9|6.1|7.6|6.6|
|Output (PPP)|4.1|5.6|6.1|6.8|5.7|4.5|5.4|6.2|6.5|5.7|5.0|
|Output per capita (PPP)|1.7|3.2|4.2|5.5|3.6|2.0|3.0|4.3|5.2|3.6|3.0|
|**Sub-Saharan Africa**||||||||||||
|Output|2.5|2.2|4.0|3.7|3.1|2.0|2.7|4.3|3.4|3.1|3.8|
|Output per capita|-0.2|-0.7|1.3|0.9|0.3|-0.7|-0.2|1.6|0.6|0.3|1.1|
|Industrial production|...|...|...|...|...|...|...|...|...|...|...|
|Trade|3.9|1.0|7.2|3.6|3.9|4.9|2.2|7.9|3.1|4.5|4.3|
|Output (PPP)|2.5|2.3|4.1|3.9|3.2|2.0|2.9|4.4|3.6|3.2|3.9|
|Output per capita (PPP)|-0.3|-0.6|1.4|1.1|0.4|-0.8|-0.1|1.7|0.8|0.4|1.1|

Note: All variables show percent changes. See footnote of Table 9. Regional aggregates include EMDEs only.

59
AAMY designed a field experiment that offered new facilities for Salvadoran migrants to directly channel some fraction of their remittances into savings accounts in El Salvador. Savings facilities were offered in conjunction with Banco Agricola, El Salvador’s largest bank. To isolate the importance of migrant control over savings, AAMY test demand for different products that offer migrants varying levels of control. For example, they investigate differential demand for savings accounts that must be solely in the name of a remittance recipient in El Salvador, versus accounts that are either jointly owned with the migrant or for which the migrant is the sole owner.

The impact evaluation uses a randomized treatment-control methodology. Migrants in the study are randomly assigned across treatment conditions, and so comparisons across the various treatment conditions reveal the causal impact of offering migrant control on the outcomes of interest (which include savings account take-up, savings balances, and remittances). The intervention studied is unusual among development economics field experiments in that it is conducted among migrants who are located in a developed country, while several primary outcomes of interest (savings) are those of individuals who remain behind in a developing country. Data on activity at our partner bank are available from the bank’s administrative records. Baseline and follow-up surveys administered to both migrants in the U.S. and their corresponding remittance-receiving households in El Salvador provide data on a broader set of other outcomes.

AAMY’s results provide evidence that a desire for control over remittance uses—in particular, control over the extent to which remittances are saved in formal savings accounts—is quantitatively large and has an important influence on financial decision making by migrants. Across the experimental conditions in the sample, migrants were much more likely to open savings accounts when offered the option of greater control over the accounts. What’s more, offering greater migrant control over El Salvador-based savings accounts led to higher savings accumulation in El Salvador.

A related randomized experiment on savings among immigrants was conducted by Chin, Karkoviata, and Wilcox (2010). This study examines the impact of providing Mexican immigrants in the US with assistance obtaining a form of ID (a _matricula consular_ ) that can be 17
# **Figure 7: Number of Female and Male New Hires in Grades GB, GH and GF, GG: 1988-2015**

<!-- Start of picture text --> 200<br>180<br>160<br>140<br>120<br>100<br>80<br>60<br>40<br>20<br>0<br>Male Female<br>No. of People Hired<br>1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015<br><!-- End of picture text --> <!-- Start of picture text --> 45<br>40<br>35<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>Male Female<br>250<br>200<br>150<br>100<br>50<br>0<br>19<br>Male Female<br>No. of People Hired<br>1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015<br>No. of People Hired<br>1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015<br><!-- End of picture text --> <!-- Start of picture text --> 200<br>180<br>160<br>140<br>120<br>100<br>80<br>60<br>40<br>20<br>0<br>Male Female<br>No. of People Hired<br>1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015<br><!-- End of picture text -->
predictions of CDM diffusion are consistent with the historic pattern of growth in CDM projects and behave according to conceptual models of technology diffusion. We fit a sigmoid expansion path model to historic CDM expansion data and test whether the predicted size of the CDM market will be exceeded during the first commitment period of the Kyoto Protocol and beyond. Estimates of the future size of the CDM market are of paramount importance to investors and policy makers as both groups are concerned with the attractiveness of the CDM mechanism. One of the questions discussed in the UNFCCC Conference of the Parties (COP) in Copenhagen in December 2009 is whether or not CDM should remain one of the major mechanisms to allow countries reduce the cost of meeting their emission reduction targets. The answer to such question may rely heavily on the trends of the CDM market, as predicted in our analysis.

The remainder of the paper is organized as follows. The next section presents a brief review of relevant literature on diffusion of technologies. Section three examines the mitigation potential of the CDM and presents the available estimates of the size of the CDM market. Section four describes the CDM pipeline data and presents the empirical results for the CDM diffusion pattern along with projections of CDM activity during and beyond the first commitment period of the Kyoto Protocol. The last section discusses the policy implications, indicates areas of future research, and concludes.

# **Technology Diffusion Literature**

Various models of diffusion have been developed to explain changing populations, technology diffusion, and adoption of new consumer products. All of those models are founded on theories concerning the spread of information either through interactions between adopters and non-adopters or through exogenous sources (Feder and Umali, 1993). Aggregate models on technology diffusion are founded upon the epidemic or logistic model<sup>7</sup> . The logistic model views the diffusion process to be similar to the spread of an infectious disease, with the analogy that contact with other adopters (i.e., learning from the experience of others) and exposure to information on the innovation (i.e., demonstration effect) leads to adoption. The model is based on the assumption that members of a

> 7 See, for example, Griliches (1957, 1980), Mansfield (1961), Gore and Lavaraj (1987), Doessel and Strong(1991), Knudson (1991) and Danar and Yaron (1992).

4
Excessive credit growth can threaten macroeconomic stability in many ways. Given that lending supports consumption, growth in private sector loans can overstimulate aggregate demand beyond the potential output and cause the economy to overheat, with subsequent effects on inflation, the current account deficit, interest rates, and the real exchange rate. At the same time, lending institutions can, in an economic growth phase, have overoptimistic expectations about borrowers’ future ability to repay their debts and therefore very often lend to high-risk borrowers. The upshot is that the bulk of ―potentially‖ bad loans arise during upward phases of the credit cycle. An analysis of corporate loans’ monthly default rates shows that loans provided in the major boom years 2006 and 2007 defaulted at a higher rate than loans provided earlier (Chart 16).

**Chart 15. Prices of flats in the Czech Republic Chart 16. Monthly default rate by vintage of (2005 = 100) loans, (corporate loans only; in %)**

<!-- Start of picture text --> 0.8<br>180<br>0.7<br>160<br>0.6<br>140<br>0.5<br>120<br>0.4<br>100<br>0.3<br>80<br>0.2<br>60<br>0.1<br>40<br>I/00 I/02 I/04 I/06 I/08 I/10 0.0<br>01/09 05/09 09/09 01/10 05/10 09/10 01/11<br>Flats (Czech Rep.) Flats (Prague only) 2004 2005 2006 2007<br>Source: CZSO, CNB<br>Source: CNB, CNB calculation<br><!-- End of picture text --> The explanations provided above reveal that the Czech Republic and its central bank, unlike some other countries in the CEE region, did not resort to any supervisory or administrative measures to tame the credit boom. The only measures of a macroprudential kind consisted of open communication and public warnings. Still, the consequences of the crisis were relatively contained, and the banking sector was able to provide credit throughout without major disturbances. Particular qualities of the credit boom in the Czech Republic relative to those in other converging economies have been to a large extent associated with the specific macroeconomic environment in which the Czech economy has been operating. Prudent macroeconomic policies and tough monetary conditions were the key ingredients of the macroprudential policy toolkit. At the same time, as well as during the 2008–2009 crisis, the fact that both monetary policy and banking supervision have always been the responsibilities of the central bank proved to be rather important. With the benefit of hindsight, one can say that the specific macroeconomic environment has had a strong impact on the risks associated with the operation of the banking sector, its lending activity, and its policy reaction to the credit boom phenomenon. We attempt to explain the actual working of this environment in the next section.

# **4. Inflation Targeting, Currency Appreciation, and Credit Dynamics**

10
overall consumption level will also increase at the average rate of the rate of increase in workers” and retirees” consumption (Figure 9).

**Figure 8. Consumption Increases as a Result Of High Oil Revenue, but More So for** **<u>Retirees Than Workers</u>**

<!-- Start of picture text --> 15%<br>13%<br>11%<br>8.9% 9.3%<br>9%<br>7%<br>5%<br>3%<br>1%<br>-1% 2% 3% 4% 5% 6% 7% 8% 9% 10% 11% 12% 13% 14% 15%<br>Oil revenue as a share of output<br>Change in workers' consumption Change in retirees' consumption<br>Change in consumption<br><!-- End of picture text --> Source: Author’s simulations based on a general equilibrium OLG model calibrated for Brazil.

The economic rationale behind a larger increase in consumption for retirees than workers is the following: As the share of oil revenue in output increases, private saving is being crowded out since workers realize that they will both receive a transfer from the government in their working age as well as in the old age. Workers therefore reduce saving and, since oil revenue is initially assumed not to be invested, the capital stock will be crowded out in line with the crowding out of private saving.

These dynamics lead to a lower capital-labor ratio which consequently reduces the premium on labor and increased the return to saving. As a result, workers receive a higher “oil transfer” from the government that boosts their consumption but there is a counteractive effect originating from a lower wage rate. The opposite is true for retirees; they also receive a transfer from the government but the return on their savings increases leaving them even better off. The end result is that both generations’ consumption levels increase — but workers gain less than retirees (Figure 10).

This result depends on partly on the assumption that none of the oil revenue is invested. However, if some share is invested, then the crowding out of the capital stock as well as the generational transfers will be lower. This will entail that the effect on factor prices is smaller — but the direction of the effects will still be the same. The consequence is that workers will still gain from higher oil revenue but not to the same extent as retirees.

21
# **Table 5: Sex-Differential Fertility Stopping Behavior and Effect of the Islamic Inheritance Rule: Child-Level Estimates**

||(1)|(2)|(3)|(4)|
|---|---|---|---|---|
||Act<br>|Dependen<br>ual Proportion<br>upto Chi<br>|t Variable:<br>of Sons Ever<br>ld’s Birth<br>|Born<br>|
|2 Children|-0.25***|-0.25***|-0.26***|-0.27***|
||(0.0080)|(0.0083)|(0.014)|(0.032)|
|3 Children|-0.31***<br>(0.0091)|-0.31***<br>(0.011)|-0.31***<br>(0.016)|-0.29***<br>(0.034)|
|4 Children|-0.36***<br>(0.012)|-0.36***<br>(0.016)|-0.36***<br>(0.020)|-0.36***<br>(0.039)|
|5 Children|-0.38***|-0.38***|-0.39***|-0.36***|
||(0.014)|(0.018)|(0.025)|(0.036)|
|6 Children|-0.41***|-0.41***|-0.41***|-0.39***|
||(0.020)|(0.023)|(0.029)|(0.045)|
|7 Children|-0.42***|-0.42***|-0.45***|-0.43***|
||(0.023)|(0.028)|(0.034)|(0.048)|
|8 Children|-0.45***<br>(0.032)|-0.46***<br>(0.037)|-0.48***<br>(0.044)|-0.46***<br>(0.072)|
|Muslim* At least one brother at||-0.078|-0.12|-0.11|
|child birth||(0.080)|(0.11)|(0.18)|
|Muslim * At least one brother at||-0.042*|-0.049|-0.12*|
|child birth* Child birth after 1994||(0.021)|(0.033)|(0.048)|
|Muslim* At least one brother at||0.13|0.14|0.22|
|childbearing||(0.082)|(0.12)|(0.18)|
|Muslim * At least one brother at||0.047|-0.38***|-0.48***|
|childbearing * Childbearing after 1994||(0.043)|(0.087)|(0.14)|
|Mean, dependent variable|0.81|0.81|0.77|0.69|
|R-squared|0.41|0.42|0.39|0.25|
|Observations|20136|20090|7671|1931|
|Sample|All children|All children|Mother age<br>40 to 49|<br>Last child<br>and no<br>desire for<br>more|

* p<0.05,  ** p<0.01,  *** p<0.001.

Note: OLS estimates of interactions between indicators of Muslim religion, having at least one surviving brother and whether birth occurred in post-compilation period, evaluated at both the time the couple started childbearing and the time of child birth. Parentheses contain standard errors clustered at the PSU-level. Regressions use survey weights. Baseline sample excludes children born to mixed-religion and polygamous couples. Columns (1) and (2) report estimated coefficients for the entire sample of children. Columns (3) reports estimates for a sample of children born to women who are 40 to 49 years old; and column (4) for the last children born to women who have no desire or who cannot continue childbearing. All regressions include fixed effects for the men’s total number of siblings at the time the couple started childbearing and at the time of child birth, the year of first child birth, the year of birth of the child, the women’s age, and area and region of residence. Other controls included are men and women’s educational attainment and indicator of household wealth. Data summary is provided in Appendix 1.

36
18 manufacturing average was only 0.7%. In the basic manufacturing industries the expenditures ranged between 1% and 2.2% of output in 1988. These have increased in Germany in recent years where many basic industries have allocated 10-16% of their investment to environmental protection. Nevertheless, their overall of expenditures remain moderate. Despite the higher than average environmental expenditures in the sensitive industries and the overall increases in recent years the trade data and correlation analysis (see above) show little impact on export performance. Germany maintained competitiveness in the sensitive goods (Table 2) over the past two decades.

In other countries as well trade data shows little impact of these costs on trade performance in these sensitive industries (see above). As private environmental expenditures seem to be lowest in Japan and total expenditures have declined, the fact that Japan has lost comparative advantage in many environmentally sensitive industries is unlikely to have been due to higher environmental costs. A more likely explanation could be that Japan decided to move out of energy-intensive smelting and refining industries. These were also the most polluting.

In the United States there has been no major shift in con., rative advantage in the sensitive industries (RCA index remained at 0.8), despite the relatively ligh private environmental costs. Despite an increase in total environmental costs in Austria during the 1980s, it increased competitiveness in environmentally sensitive industries. The correlation between environmental costs and competitiveness was even positive. In the Nordic countries the public share is relatively high and environmental costs declined overall during the 80s. But this is unlikely to explain the increased market shares in these products.

The Japanese case suggests that pollution-intensity and **energy-intensity** are highly correlated. The link can be direct or indirect. environmental expenditures can have an indirect impact on energy costs, and vice versa. In Japan and Germany, for example, in the mid-1980s electricity and utilities accounted for over half of total environmental investments in industry. In Germany, the electricity and mining sectors devoted nearly 20% of their investment to environmental protection in 1990. As utilities tend to have the highest environmental
percent by 2004 (Behrman et al. (2008)).<sup>41</sup> The increased monetary costs of education naturally increased the persistence in educational attainment across generations; only the relatively rich in rural areas could afford higher education. After the economic reform in 1978, the relatively educated parents could take full advantage of the new opportunities both in agriculture and the non‐farm sector, and thus they reaped high income. Yang (2004) shows that the more educated people were able to allocate their resources more efficiently under the household responsibility system (see also Li and Zhang (1998)).<sup>42</sup> This higher income allowed them to invest in children’s education in the face of increasing private cost of schooling. The disadvantage faced by the children of less educated (and thus poorer) parents was reinforced by the rising returns to working in the rural non‐farm sector (or urban migration); the opportunity costs of not working along with higher monetary costs of education made it difficult for them to continue schooling beyond a low threshold (primary schooling for example). Another factor that may have contributed to the educational immobility is the increasing returns to education in rural China following the economic reform (Behrman et al. (2008)). As shown by Solon (2004) higher returns to education are expected to increase the persistence in intergenerational economic status.

# **6. Conclusion**

Using two rounds of CHIP household survey data for 1988 and 2002, this paper provides evidence on the evolution of intergenerational economic mobility in rural China. It aims to answer the following question: has the rural society in China become more or less mobile from 1988 to

> 41 For detailed and in‐depth evidence on the importance of fees and related costs in schools of rural China, see Hannum (2008).

> In a World Bank report, Piazza and Liang (1998) conclude that “despite the extraordinary success in basic education in China, many poor were not reached by the government efforts...in the poorer half of the townships of 35 counties supported by a World Bank projects, average enrollment was at least 10 % points lower than the national average for the same age group...".

> 42 The returns to education was, in contrast, very low under collective agriculture before 1978.

38