rafmacalaba/datause-encoder-data huggingface dataset:
71 More generally, individual level data often show father's education is also a stimulus to the child's achievements in school.

King at **al.** (1986) estimated from several Asian surveys the determinants of parents' investing in the schooling for their children, and how they respond differently toward the schooling of girls and boys. Analysis of schooling decisions from a Peruvian survey permitted **the** analysis of whether the parents invest by sending their children away to continue their schooling, generally at a private versus local public school. Aialysis of the schooling decision suggests that community school access and family income both increase enrollments, particularly for girls (King and Bellew, 1988; Gertler and Gleewe, 1988).

In most studies of schooling of children in high income countries, the mother's schooling has a larger effect than **the** father's, **even** though the father's education implies a larger market income effect, because he tends to receive a higher wage and work more hours in the labor force (Leibowitz, 1974; King et al., 1986). The evidence that mothers' schooling exerts a greater effect on the schooling of their daughters than their sons is less well established (e.g. DeTray, 1988): Table 5). It is a hypothesis that needs further study.

# Determinants of Fertility

Fertility is generally observed to decrease as women's education increases. Occasionally, however, fertillity of imnschooled women is lower than that of women with a few years of primary education (Cochrane, 1979). A husband with more schooling (or income) in traditional agricultural societies is frequently observed to have a larger family as noted previously. But spouses of similar education tend to marry. Because of the general positive
the ages of 18 and 64 and has taken some action towards starting a business in the last year, and expects to own or share the business they are starting, which must not have paid any wages of salaries for more than 3 months (nascent startups). The second definition uses the standard definition of entrepreneurship with the additional requirement that the entrepreneurs expect to create ten jobs or more within the next five years, a definition also used by Estrin and Mickiewicz (2011) to identify high aspiration entrepreneurs. The cut-off point of ten jobs or more was selected as it is consistent with the standard distinction between small and micro enterprises. In our sample, the mean percentage is 4.8% for nascent startups and 1.6% for high aspiration startups.

We obtain government spending data on private subsidies from the International Monetary Fund’s Government Financial Statistics (GFS). Our key variable of interest is the share of government spending on private subsidies over total government spending. We define government spending in private subsidies as spending on agriculture, forestry (timber), hunting, fishing, wildlife, energy and fuel, manufacturing, mining, and defense spending. The advantage of using the shares of spending is twofold – first we obtain unit free measures of spending devoid of currency and inflation fluctuations, and second we identify the source of financing of private subsidies being all other types of government spending given that we control for total government consumption in the estimations. In the sample, the share of private subsidies in government spending has a mean of 8.6% with the minimum being 2.1% (Ireland) and the maximum being 31.6% (Syria).

We control for several macro-economic factors such as the level development of the economy and as well as the quality of institutions. We also include controls for individual characteristics such as education, age, and connection to networks. Our choice of control variables are the same as those used in the literature (Estrin and Mickiewicz, 2011; Aidis et al., 2012). Our estimation model is a random country effects probit model with fixed year effects.

4
_1. The teacher uses questions, prompts, or other strategies to determine students’ level of understanding_ _2. The teacher monitors most students during independent/group work_ _3. The teacher adjusts teaching to the level of students_

# _1. The teacher uses questions, prompts, or other strategies to determine students’ level of understanding_

To bridge the gap between what teachers teach and what students learn, teachers need to collect data during the lesson on what are students learning. Asking students questions and checking the understanding of all students is a type of formative feedback that supports learning and has been identified as a critical component of instruction (Good & Grouws, 1977; Rosenshine, 2012). For example, in an study of Indian schools, Aslam & Kingdon (2011) compared math and language teachers on instructional performance and found positive and large effects on student learning of teacher questions and checks on understanding. It is important also for teachers to not just ask any questions (i.e., rhetorical questions such as “Everyone got it?”) but instead to ask clear questions that provide objective data on students’ understanding (Lemov, 2015). Further, compared with less effective teachers, effective teachers have been found to be more aware of students’ level of engagement in the class as a whole and are more likely to balance responses from volunteering and nonvolunteering students by calling upon students during class (Brophy & Good, 1985).

Other strategies shown to work include teachers presenting new material in small steps and checking student understanding by having students practice after each step. Such teaching practice has been found to improve student outcomes particularly for subjects like mathematics and English (Evertson, Anderson, Anderson, & Brophy, 1980).

# _2. The teacher monitors most students during independent/group work_

Whether students are completing an in-class activity individually or in a group, it is recommended that teachers monitor what students are doing rather than wait passively until students have finished with the activity before they check for students’ understanding (Lemov, 2015). For example, Knapp et al. (1995) observed classrooms in low socioeconomic neighborhoods in the United States and concluded that teachers’ active monitoring and facilitation during independent and group work ensured that students were engaged and 21
- Bloom, Nicholas, John Van Reenen, and Heidi Williams. “A toolkit of policies to promote innovation”. _Journal of economic perspectives_ , vol. 33, no. 3, 2019, pp. 163–84.

- Blundell, Richard, Rachel Griffith, and John Van Reenen. “Market share, market value and innovation in a panel of British manufacturing firms”. _The review of economic studies_ , vol. 66, no. 3, 1999, pp. 529–54.

- Boeing, Philipp, and Elisabeth Mueller. “Measuring patent quality in cross-country comparison”. _Economics Letters_ , vol. 149, 2016, pp. 145–47.

- Branstetter, Lee, Guangwei Li, and Francisco Veloso. “The rise of international co-invention”. _The changing frontier: Rethinking science and innovation policy_ , 2015, pp. 135–68.

- Branstetter, Lee G, Guangwei Li, and Mengjia Ren. “Picking winners? Government subsidies and firm productivity in China”. _Journal of Comparative Economics_ , vol. 51, no. 4, 2023, pp. 1186–99.

- Callaway, Brantly, and Pedro HC Sant’Anna. “Difference-in-differences with multiple time periods”. _Journal of econometrics_ , vol. 225, no. 2, 2021, pp. 200–30.

- Cerdeiro, Diego A, Johannes Eugster, Rui C Mano, Dirk Muira, and S Jay Peirisa. “Sizing up the effects of technological decoupling1”. _Geoeconomic Fragmentation The Economic Risks from a Fractured World Economy_ , 2023.

- Chen, Jiafeng, and Jonathan Roth. “Logs with zeros? Some problems and solutions”. _The Quarterly Journal of Economics_ , vol. 139, no. 2, 2024, pp. 891–936.

- Coe, David T, and Elhanan Helpman. “International r&d spillovers”. _European economic review_ , vol. 39, no. 5, 1995, pp. 859–87.

- Coelli, Federica, Andreas Moxnes, and Karen Helene Ulltveit-Moe. “Better, faster, stronger: Global innovation and trade liberalization”. _Review of Economics and Statistics_ , vol. 104, no. 2, 2022, pp. 205–16.

- De Rassenfosse, Ga`etan, Helene Dernis, Dominique Guellec, Lucio Picci, and Bruno Van Pottelsberghe De La Potterie. “The worldwide count of priority patents: A new indicator of inventive activity”. _Research Policy_ , vol. 42, no. 3, 2013, pp. 720–37.

29
Table 14: **Value added shares of exports by sector – China**

|||1992|1995|1997|2004|2007|
|---|---|---|---|---|---|---|
|China|Primary|0.474|0.342|0.366|0.300|0.281|
|Direct VA share|Textiles and Clothing|0.226|0.159|0.240|0.195|0.196|
||Machinery|0.257|0.210|0.234|0.179|0.183|
||other Manufacturing|0.260|0.195|0.265|0.257|0.252|
||Trade and Transport Services|0.509|0.445|0.444|0.492|0.482|
||Commercial Services|0.633|0.429|0.396|0.523|0.512|
||Public Services|0.560|0.453|0.441|0.553|0.548|
|||1992|1995|1997|2004|2007|
|China|Primary|1.406|2.114|1.974|2.234|2.554|
|Total VA share|Textiles and Clothing|0.295|0.249|0.428|0.354|0.369|
||Machinery|0.355|0.365|0.391|0.279|0.290|
||other Manufacturing|0.515|0.534|0.651|0.753|0.676|
||Trade and Transport Services|285.847|2.200|1.391|1.551|1.492|
||Commercial Services|1.030|3.292|4.513|4.738|4.036|
||Public Services|8.224|1.093|1.050|1.459|1.687|

Table 15: **Relative intensity index based on forward linkages – China**

|||1992|1995|1997|2001|2004|2007|
|---|---|---|---|---|---|---|---|
|China:|Primary|0.340|0.240|0.221|0.190|0.195|0.184|
|RII|Textiles and Clothing|0.143|0.107|0.166|0.152|0.097|0.087|
||Machinery|0.079|0.116|0.148|0.173|0.174|0.172|
||other Manufacturing|0.157|0.199|0.233|0.255|0.247|0.255|
||Trade and Transport Services|0.088|0.185|0.145|0.127|0.130|0.128|
||Commercial Services|0.190|0.143|0.081|0.096|0.142|0.160|
||Public Services|0.005|0.009|0.006|0.007|0.014|0.013|

23
<!-- Start of picture text --> 2 1.0<br>0<br>-2 -1.1<br>-4<br>-3.9<br>-6 -4.8<br>-8<br>-10 -8.9<br>Total Savings Household Public Household Private Corporate<br>Financial Physical<br><!-- End of picture text --> Note: Data is from CEIC. Figures show the difference between the average rate in 2016 and 2017, over 2007 and 2008.

The investment rate has declined as well since the GFC, after registering a rapid increase in prior years. The decline is most evident in the corporate investment and household physical investment rates. There is a divergence in the corporate savings and investment rate, since while the corporate savings rate has increased, its investment rate has declined.

**Figure 18: Trends in Investment Rate**

18 A: The investment rate has declined since the 18 B: ...the decline is evident in household GFC... investments...

<!-- Start of picture text --> Investment as percent of GDP<br>40<br>35<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>18 C: ...and private corporate sector<br>2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017<br><!-- End of picture text --> <!-- Start of picture text --> Household Sector Investment<br>18<br>16<br>14<br>12<br>10<br>8<br>6<br>4<br>2<br>0<br>2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017<br><!-- End of picture text --> 18 D: While public investment fell after GFC, it has increased modestly in recent years 34
# 3. Decomposing the Capital Income Share

While we were able to measure labor income shares directly from observed earnings data, estimating the payment to different types of capital requires a more structural approach. With a single type of physical capital—as is customary in most macro analyses—it is straightforward to measure the capital income share as one minus the labor income share. However, we are interested in separating the payments to several distinct types of capital. The payment to each type of capital is comprised of both a unit payment (the rental rate of capital) and the (real) stock of capital— analogous to the wage rate and the physical amount of labor provided by the worker. Both of these items are challenging to measure, especially when the relative prices of the various types of capital are changing over time.

We build on two standard assumptions, that have been used to measure the returns to capital at least since the seminal work by Hall and Jorgenson (1967) and Christensen and Jorgenson (1969), which allow us to directly measure capital type specific income shares from the BEA’s current cost values for the stocks of detailed assets in the US.<sup>15</sup> Specifically, we impose a no-arbitrage condition in investment in addition to the standard constant returns to scale assumption.<sup>16</sup> Suppose that there are several types of capital, denoted _Ki_ , with _i_ = 1 _, ..., I_ . If the production technology exhibits constant returns to scale in all factors, the share of payments to capital must satisfy the following equilibrium relation: where _sK,t_ and _sL,t_ denote the aggregate capital and labor income shares, respectively, _Yt_ is final

> 15Official documenation for the BEA’s methodology to construct these estimates is available at http://www.bea.gov/national/pdf/Fixed ~~A~~ ssets ~~1~~ 925 ~~9~~ 7.pdf. Most macroecnomic studies using capital stocks utilize a simpler version of the perpetual inventory method than the BEA’s estimates, usually based on linear constant depreciation and aggregate real investment rates. We prefer the BEA’s estimates for several reasons: first, they are provided at the detailed asset level; second, they allow for time varying non-linear depreciation patterns; finally, these estimates allow us to directly use nominal stocks at current cost, rather than chain-weighted quantity indexes.

> 16For a few more recent contributions that use the same basic strategy to compute the return to specific types of captial in various contexts see for example Jorgenson (1995), O’Mahony and Van Ark (2003), and Caselli and Feyrer (2007). We outline the basic idea of our implementation to measure capital type specific income shares here and provide detailed derivations in Appendix A.

16
King, E, Rawlings, L, Gutierrez, M, Pardo, C and Torres, C (1997): “Colombia’s targeted education voucher program: features, coverage and participation”, The World Bank Working Paper Series on Impact Evaluation of Education Reforms, N.3, Washington DC King, E. and Ozler, B. (1998) “What’s decentralization got to do with learning? The case of Nicaragua’s School Autonomy Reform”, The World Bank Working Paper Series on Impact Evaluation of Education Reforms, N.9, Washington DC King, E, Orazem, P and Wohlgemouth, D (1999): “Central mandates and local incentives: the Colombian education voucher program”, in the _<u>World Bank Economic Review</u>_ <u>, Vol.13, N.3, pp. 467-491</u> Klugman, J (1994): “Decentralization: a survey of literature from a human development perspective”, Human Development Report Office Occasional Papers, UNDP, New York.

McEwan, P and Carnoy, M (1999a): “The Impact of Competition on Public School Quality: Longitudinal Evidence from Chile’s Voucher System”, Stanford University, ( _mimeo_ ).

McEwan, P and Carnoy, M (1999b): “The effectiveness and efficiency of private schools in Chile’s voucher system”, Stanford University, ( _mimeo_ ).

Paes de Barros, R and Silva Pinto de Mendonca, R (1998): “The impact of three institutional innovations in Brazilian education “ in Savedoff, W.D, ed, _<u>Organization matters: agency problems in health and education</u>_ <u>, Inter-American Development Bank, Washington DC</u> Rounds, T (1997): “Achieving balance in decentralization: a case study of education decentralization in Chile”, in _<u>World Development</u>_ <u>, Vol. 25, N.2</u> Ruiz, F and Giussani, B (1997): “El Proceso de Descentralizacion y el Financiamento de los Servicios de Educacion y Salud en Bolivia”, Serie Reformas de Politicas Publicas N.48 -ECLAC, Chile Sapelli, C and Vial, B (2002): “The performance of private and public schools in the Chilean voucher system”, in _<u>Cuadernos de Economia</u>_ <u>, Year 39, N.118, pp.423-454</u> Sawada, Y and Ragatz, A (2004): “Decentralization of Education, Teacher Behavior, and Outcome: The Case of El Salvador’s EDUCO Program”, The World Bank, _(mimeo)_ Schiefelbein, E and Schiefelbein, P (2000): “Three decentralization strategies in two decades: Chile 1981-2000”, in _<u>Journal of Educational Administration</u>_ <u>, Vol.38, N. 5</u> The World Bank (1999): _“Beyond the Center: Decentralizing the State”_ , WashingtonDC The World Bank (2003): “ _<u>Brazil Municipal Education: Resources, Incentives and Results</u>_ ”, The World Bank, Washington DC The World Bank (2004): “ _<u>Making Services Work for Poor People</u>_ ”, The World Bank and Oxford University Press, Washington DC 33
- 14 -

<!-- Start of picture text --> Figure 2. Interest Rate in Thailand Around<br>the Time of the Reform<br><!-- End of picture text --> <!-- Start of picture text --> 20-<br>12 i_ DEP<br>I8<br>4<br>2-<br>'M Moncy0Market mmt<br>LRATE Lending rate<br>;-RSGP Singapore Money Marcet rate<br><!-- End of picture text -->

# EFS Data
fully admitting to IPV experiences and that the empirical results are capturing only a subset of the changes that are actually occurring.

# **Section 8. Mechanisms for the Decline in IPV**

We also investigate a potential mechanism for the observed changes. In the Introduction, we noted that disasters have the potential to substantially change the tasks needed to be performed by the entire household, which has the potential to change the roles and responsibilities of each household member. Thus, although there are reasons that negative economic shocks and increased stress might worsen IPV attitudes and prevalence, these added roles and responsibilities that women might support might actually improve their importance and standing in the household.

Although most of the intrahousehold roles and responsibilities are difficult to observe in a household survey, we do find evidence of an expanded role for women inside the household. The survey asks women who in the household is primarily responsible for four different decisions- how to spend a husband’s income, health decisions for the respondent, large household purchases, and for decisions about visiting other family members. For all four decisions, we re-estimate the baseline specification using indicators equaling one if the husband alone was responsible for the decision and indicators equaling one if the wife was alone responsible for the decision.

Figure 10 illustrates that there was a reduction in the instances in which the husband was solely responsible for each decision. The larger decline in the shares in disaster-affected regions varied between 3 and 16 percentage points, which represents between 9 and 34 percent of the pre-disaster shares in disaster-affected regions; and two of the four estimates are precisely estimated and are statistically significant at conventional significance levels (p-values of 0.035 and 0.051). Furthermore, the estimates for men being solely responsible for decisions are accompanied by an increase in the share of women who are alone responsible for each decision.

Although we are unable to list all the potential reasons for why IPV attitudes and IPV prevalence declined following the disaster, the results suggest a key pathway- an expanded role for women in a very tumultuous setting. More fully uncovering what these added roles and responsibilities are inside the household in disaster settings, and comparing these added roles to other potential factors that could aggravate IPV, could more fully explain some of these patterns and the instances in which the prevalence of IPV might actually decline in disaster settings.

# **9. Conclusion**

This analysis illustrates that attitudes about IPV substantially improved following a large disaster 21
interesting, therefore, to investigate whether migrants send money home as an insurance against the vulnerable nature of their position at the destination location.

# **3. Data**

The empirical analysis reported in this paper is based on data from the 2004 Vietnam Migration Survey. The survey was undertaken by the General Statistical Office (GSO) of Vietnam with the aim to provide detailed information on internal migration in the post _doi moi_ era (GSO, 2005). It was conducted in areas identified with high immigration rates based on the 1999 Population and Housing Census, and the sample was selected using the sampling frame of the Population Census (see GSO, 2005). They included some enumeration areas of Hanoi, the Northeast Economic Zone (Hai Phong, Hai Duong and Quang Ning), the Central Highlands (Gia Lai, Dak Lak, Dak Nong and Lam Dong), Ho Chi Minh City, and the Southeast Industrial Zone (Bing Duong and Dong Nai).

The survey interviewed both migrants and non-migrants in the destination areas, who were in the 15 to 59 age-group category. In this survey we restrict our analysis to migrants, and these are defined as those who had moved from one district to another in the five years prior to interview but not more recently than a month before the interview date. The survey covered a wide range of topics including information on the migration process, socioeconomic characteristics of migrants, demographic composition of household members (at the destination), housing conditions, access to public services, and personal history (e.g., migration and employment activity) of migrants.

10