rafmacalaba/datause-encoder-data huggingface dataset:
**Fiscal Aggregates as Percent of GDP: 1995-2006**

<!-- Start of picture text --> 30%<br>25%<br>20%<br>15%<br>10%<br>5%<br>0%<br>-5%<br>-10%<br>-15%<br>1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006<br>Expenditure Domestic Revenue Domestic Financing Fiscal Deficit<br><!-- End of picture text --> Source: IMF Given that the economy has begun to recover strongly from the contraction of the first half of the 1990s, it is pertinent to ask what role fiscal policy played in the recovery. The main channel through which fiscal policy supported the economic recovery was through improved macroeconomic stability brought about by fiscal adjustment. The strong GDP growth achieved during the 2000s was preceded by a substantial fiscal adjustment in the second half of the 1990s, which enabled government to cut its domestic borrowing sharply. Segura-Ubiergo, Simone and Gupta (2006) examined the relationship between fiscal adjustment and growth in CIS countries during the period 1992-2001, finding a strong correlation between fiscal adjustment and growth in those countries which needed to attain macroeconomic stability. They hypothesize that fiscal adjustment in the CIS countries boosted economic growth through two channels; the reduction in government borrowing requirements and associated monetization of deficits, and a credibility effect which signaled government commitment to macroeconomic stability and sound fiscal policy. This in turn stimulated an expansion of official and private capital inflows (boosted in the case of Tajikistan by workers’ remittances) that at least partly substituted for the loss of 5
with the perspectives underlying the Bank’s strategy. It is now a widely held view that directed credit systems are considerably less resilient and more prone to shocks. As the increasing IFC role suggests public sector housing banks are gradually being superceded by market-oriented private lenders. Finally, the wide-spread adoption of housing vouchers as the central vehicle to provide housing subsidies across almost all developed economies (see Boelhouwer (1997)) implies a similarly wide-spread recognition of the superiority of transfer mechanisms that use market incentives. This is a welcome change to mechanisms that replaced market incentives, as many public housing programs did even in OECD countries in the 1980s and early 1990s.

In sum, shelter policy has indeed evolved over recent years. Perhaps the foremost lesson we have learned is that the maintained hypothesis of the Bank’s shelter policy has been confirmed – a targeted and limited public role is a sine qua non for a wellfunctioning housing sector. At the same time, there is no mysterious, straightforward capitalist panacea that can address all of the shelter problems faced by low-income families in developing countries. Circumstances vary widely and policy must be designed to exploit local conditions. Just providing titles, for instance, will not magically transform the housing situation of the poor. We have also achieved a better empirical understanding of the sometimes profound effects that regulatory policies can have on the functioning of housing markets, and a much stronger sense of the need to incorporate the views of the poor in how to effectively address their concerns. Increased community involvement is not only good social policy, it also improves project performance.<sup>27</sup> This

> 27 A recent Bank study “Overview of the World Bank’s Experience in Urban Projects with Community Participation” found that 31 percent of Urban Projects in the 1991-2001 period has a Community Participation component compared to 11 percent on the 1981 –1990 period.  In the 1991-2001 period, projects which had a community participation component were found to have a satisfactory outcome rate of 86 percent when compared to all urban projects which had satisfactory outcome rates of 71 percent.

26
trademarks, another TRIPS-Plus standard. Finally, the agreement set out minimum protection of geographical names through systems quite similar to those covering trademarks and collective marks. Trade agreements negotiated by the EU and EFTA in this era had similar requirements, though they emphasized somewhat different areas of concern, most prominently in establishing specific systems for recognizing and protecting GIs.

NAFTA was preceded by the formation of the European Economic Area (EEA) in 1994, linking three members of EFTA to the EU’s single-market program. Over time, an essential component of policy making in the EEA has been the adoption of stronger and more harmonized intellectual property standards throughout the region.

The subject matter coverage of PTAs sharply increased after 2000, with the United States and the EU demanding stronger and more comprehensive IPR provisions. Moreover, other new PTAs, not involving the United States or the EU, were negotiated by Japan, Australia, Korea, Mexico, and Chile, among others. These PTAs also included IPRs chapters, though typically with less rigorous standards in certain areas.

It is important to note that most of these IP-related PTAs are legally enforceable, as designated in the World Bank data. Specifically, the database ranks the legal enforceability (LE) of PTAs on a scale of 0, 1, or 2, with 0 essentially indicating that no enforcement language exists, 1 describing weak enforcement language (e.g., “should” or “may”), and 2 identifying those with clear commitment language (e.g., “shall” or “must”). We use this designation (LE = 2) as one means of selecting the treatment IPAs in the econometric analysis.

Figure 1 illustrates the considerable growth since 1990 in the number of IPAs in the World Bank data that feature strong enforceability.<sup>2</sup> The red lines indicate the number of agreements, and the blue lines show the number of countries in one or more of them.<sup>3</sup> As depicted in panel (a), the number of IPAs rose from fewer than 20 in 2000 to 100 in 2015, while the number of countries involved now exceeds 100. Thus, currently around two-thirds of WTO

> 2 Appendix Table A1 gives the full list of IP-related PTAs and the year in which each agreement entered into force. 3 An important related source of information is the DESTA database described in Dür et al. (2014). It defines IPAs as agreements with an IPRs chapter, regardless of how comprehensive or rigorous.

4
# _Table 3. Treatment effect on school enrollment_

Dependent variable is: “Is the child enrolled and going to school”. Dprobit, marginal effects.

||(1)|(2)<br>All child|(3)<br>ren|(4)|(5)<br>Children aged 8|(6)<br>to 12|
|---|---|---|---|---|---|---|
||All Sample|All Sample|Leaving out untreated<br>HH in treated villages|All Sample|All Sample|Leaving out untreated<br>HH in treated villages|
|Treated*Endline|0.118<br>(0.0416)***|0.125<br>(0.0444)***|0.124<br>(0.0429)***|0.143<br>(0.0397)***|0.146<br>(0.0473)***|0.151<br>(0.0417)***|
|Endline|0.241<br>(0.0339)***|0.241<br>(0.0339)***|0.241<br>(0.0341)***|0.222<br>(0.0338)***|0.222<br>(0.0339)***|0.223<br>(0.0339)***|
|Girl|-0.0640<br>(0.0134)***|-0.0617<br>(0.0152)***|-0.0666<br>(0.0145)***|-0.0664<br>(0.0178)***|-0.0652<br>(0.0192)***|-0.0643<br>(0.0193)***|
|Treated*Girl||-0.0141|||-0.00858||
|||(0.0245)|||(0.0346)||
|Mean at baseline|||||||
|Control villages|0.4306|0.4306|0.4306|.5294|.5294|.5294|
|Treated villages|0.4118|0.4118|0.413|.5176|.5176|.5168|
|Observations<br>Individual|16,851|16,851|14,803|7,912|7,912|6,934|
|controls|yes|yes|yes|yes|yes|yes|
|HH controls|yes|yes|yes|yes|yes|yes|
|Fixed-Effects|Villages|Villages|Villages|Villages|Villages|Villages|
|Clustered-SE<br>Robust standard e|Village<br>rrors in parent|Village<br>heses. *** p<0|Village<br>.01, ** p<0.05, * p<0.1|Village|Village|Village|

<mark>Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1 Individual controls include: age, age squared, ethnicity dummies (sousou, malinke, peul, other). Household controls:household size Standard errors are clustered at the village level, for 148 villages.</mark>
_CHAPTER 6. UNIT LEVEL MODELS: GENERAL INDICATORS_ 41 type of auxiliary information is welcome as long as it is useful to predict welfare, in practice there is no guarantee that area heterogeneity has been completely accounted for by the available covariates, unless a formal statistical test for _σu_<sup>2=0wasconductedineachapplication.In</sup> any case, estimators that do incorporate area effects converge to their synthetic counterparts whenever _σu_<sup>2becomessmall,sothereisnoreason</sup> for excluding area effects.

An additional problem with the traditional ELL bootstrap method is that the noise measures delivered do not correctly estimate the true error measures of ELL estimators. The reason is that, unlike in usual bootstrap methods, the ELL bootstrap procedure does not re-fit the model and reestimate the target indicators with each bootstrap sample (which should be drawn from each bootstrap census). Hence, the real-world estimation process is not adequately replicated in the bootstrap world. As a result, the estimated MSE through this method does not accurately replicate the error incurred in estimation in the real world. Finally, when the sampling clusters are not the areas of interest, the MSE of the ELL estimator for an area indicator _δd_ can be severely underestimated if the area effects are not well explained (i.e., when their variance _σu_<sup>2issignificant).</sup> The ELL method is implemented in the `PovMap` software (Zhao, 2006), which offers a simple point-and-click user interface and is considerably fast and efficient in terms of memory. The `sae` Stata command developed by Nguyen et al. (2018) replicates most of the procedures implemented in the `PovMap` software.

Banerjee et al. (2006) conducted a review of the research at the World Bank and raised several concerns about the ELL method. First of all, they suggested that ELL was not accounting for potential area effects. This diagnosis was correct even if clusters in the ELL model are equal to the areas, because the cluster/area effects _udc_ vanish when applying ELL bootstrap procedure according to (6.3)–(6.4). They also realized that ELL estimated sampling errors were not accounting for the correlation
access to a city of more than 50,000 inhabitants, temperature, and elevation. _FE_ is the year and country fixed-effects. The coefficients _β_ capture the correlation between access to a type of infrastructure on the different sectoral employment shares, while the coefficients _γ_ capture the infrastructure interaction terms.

We identify several identification challenges. Infrastructure investments are likely endogenously allocated with respect to the outcomes of interest. Given the high cost of infrastructure investments, conscious allocation decisions are to be expected (by, for example, targeting high growth potential locations or politically demanded locations). Measurement error in the righthand side variables may lead to attenuation bias (from, for example, inaccurate information on the timing of infrastructure expansion or imprecise historic road and grid maps). Measurement errors, which are expected to be large in this case, lead to an OLS estimate that is biased toward zero.

We report results for the unbalanced panel of districts that include at least one EA. We first estimate local average associations of the three infrastructure investments—roads, electricity, and Internet—and the interaction between these investments on sectoral employment at the district-year level. Then we analyze within-country heterogeneity in structural transformation across districts. All regressions exclude the Somali region of Ethiopia, because coverage of this region in the DHS data is poor.

**Average Effects in Ethiopia and Kenya** We start with a regression that includes Ethiopia and Kenya, and then compare the results by country. Throughout, standard errors are clustered at the district level, the level of treatment. Access to roads, especially when complemented with access to electricity, is associated with a transformation away from agriculture in the Horn of Africa. Table 2 reports the results of pooling data from Ethiopia and Kenya for all years. Having access to a paved road at the district level is associated with a 4 percentage-point reduction in the employment share of agriculture and a 2 percentage-point increase in the employment share of manufacturing. Combined investments in roads and electricity are associated with a major shift from agriculture to manufacturing and services. Having access to the combined access to roads and electricity at the district level is associated with a 27 percentage-point reduction in the employment share of agriculture, a 10 percentage-point increase in the employment share of manufacturing, and a 18 percentage-point increase in the employment share of services. Results by country reported in Tables A4 and A5 in the appendix show that the impacts are similar at the country level. The combination of roads and electricity access has a large impact on structural change.

We then analyze the within-country heterogeneity in structural transformation across districts, focusing on the share of agricultural employment and the population-weighted distance to the largest town.

10
Expression (8) can be interpreted as the comparative disadvantage of the average firm relative to the leading company, adjusted by the degree of product market competition. To write expression (8) as a function of the parameters of the model; we need to characterize the distribution of quality in the steady-state. For such purpose, we employ two differential equations: and Φ _t ≡ P_ ( _qit < Q_ 0) and _Q_ 0 is the leading quality of period _t_ 0. Equation (9) says that after time _t_ 0, the rate at which vertical innovations cause the mass of products behind _Q_ 0 to fall is, in the steady-state, equal to the overall flow of vertical innovations occurring in varieties currently behind _Q_ 0. There are Φ _t_ of such goods, and the Poisson arrival rate of vertical innovations in each of these products is equal to _φ_<sup>_v_</sup> _t_<sup>.Equation(10)showsthattheleading</sup> quality grows over time as a result of knowledge spillovers in the vertical activity. The following proposition characterizes the distribution of quality in the steady-state.

**Proposition 1** _The distribution of ait ≡ Q_<sup>_<u>qit</u>_</sup> _t_<sup>_convergesmonotonicallytothe_</sup> <u>1</u> _invariant distribution_ Pr = ( _ait ≤ a_ ) = _F_ ( _a_ ) = _a γ , with_ 0 _< a ≤_ 1 _._

The methodology employed to proof proposition 1 borrows from Sergerstrom[46], and it is presented in the Appendix. Corollary 1 shows 8
and women and this in turn could be correlated with more favorable education enrollment for women. The omitted variable bias problem here is ruled out by our next control which is the (log of) the ratio of women to men in the country’s population ( _Women population_ ). We use values of the variable for the year covered by the survey. Data source is WDI.

Next, we consider institutional factors. For culture or social attitudes, we follow the literature and control for the proportion of population that is Catholic, Protestant, Muslim and Other religions. The omitted category in the regressions is Muslim population. We strengthen these controls by adding dummy variables for legal tradition of the country – English, French and Socialist (omitted category is Socialist). Data source is Rafael La Porta, Florencio Lopez-de Silanes, Andrei Shleifer and Robert Vishny 1999.

The last set of country-level controls includes two variables associated with the political structure of countries. These variables are the proportion of seats in lower house of the parliament that are held by women, _Women in Parliament_ , taken from Inter Parliamentary Union (IPU) database for the year of the survey; and the rule of law measure from Worldwide Governance Indicators (Daniel Kauffman, Aart Kraay, and Massimo Mastruzzi 2010) for the year of the survey ( _Rule of Law_ ). Justifications for the inclusions of these controls are provided in the conceptual framework.

# **4. Estimation Results**

4.1 Base regression results Regression results are provided in tables 2-4. These tables contain marginal effects or the change in the probability of a firm having a woman manager when the explanatory variable increases by 1 unit. Throughout, probability of having a top woman manager and the proportion of female top managers in the country will be used interchangeably.

17
- 31 -

monthly value of food subsidies to househoLds in the weaLthiest 20% of the population was about 53 Jamaican doLlars per capita while the same figure for the poorest 20% of the population was 29 Jamaican doLlars. In contrast, food - stamps are much more effective in reaching the poor 51% of the poorest 20% were receiving food stamps compared to only 6% of the wealthiest 20%.

TABLE 9: Incidence of Food Stamp and Food Subsidy **Benefits: Jamaica, 1988**

||||Populati|on Quinti|les||
|---|---|---|---|---|---|---|
||Poorest<br>20%|Next<br>20%|Middle<br>20%|Next<br>20%|Richest<br>20%|All<br>Jamaica|
|Value of Food|||||||
|Subsidies Received|||||||
|(Jamaican Dollars per|<br>28.6|39.6|39.5|42.5|52.5|40.5|
|person per month)|||||||
|Percent of Households|||||||
|Receiving Food Stamnp|s<br>50.6|37.1|26.3|17.0|6.0|23.4|

# F. Persistence of Poverty in Developing Countries

In developed countries, some households remain in poverty for many years, if not decades, while others move in and out of poverty over relatively short periods of time. What is the pattern found in developing countries? Most LSMS surveys are permanent surveys, i.e. they repeat every 12 months. In such cases it is useful to interview the same households in succeeding years to see how their economic status changes from year to year. In those LSMS surveys which are permanent, half the households interviewed in one year are reinterviewed in the following year. At the most simple level of analysis,
# **1. Introduction**

Technology adoption, and especially information and communication technology (ICT) adoption, has expanded dramatically during the last decade throughout the world (World Bank, 2016). Its impact on jobs and the skills that are demanded by employers is a topic of great interest as it is an important driver of future labor demand. The main concern is that the growing use of ICT at the workplace is leading to a polarization of labor markets in developed countries, whereby employment and earnings are shifting away from middle-skilled jobs into both high-skilled and low-skilled jobs (Autor and Dorn, 2013; Frey and Osborne, 2013; Autor, 2014). Some authors argue that this change is explained by <mark>changes in the task composition of jobs following digital technology adoption as computers carry out activities that follow automatized and explicit rules and procedures (Autor et al., 2003). More recently, however, technologies are advancing even faster (e.g.,</mark> robots and artificial intelligence), automating tasks that are typically performed by higher-educated workers (Brynjolfsson and McAfee, 2014; Autor, 2015). These tasks performed by technology are increasingly non-routine analytical and cognitive tasks. Examples include deeplearning systems applied to medicine, or machines being able to compose music. A crucial research and policy question is thus how these more advanced types of software and technologies are affecting the firm’s employment composition and the skill content of occupations.

To our knowledge, we are the first paper assessing the impacts of the firm’s use of more advanced technologies on the demand for skills and jobs, in the medium run. We exploit a novel firm-level survey for Chile across a six-year interval, between 2007 and 2013, when the adoption of a complex technology, such as client management, business or production software packages, is observed. We inquire whether the adoption of complex software has led to significant labor reallocation within firms on tasks with different skills contents. To date, the literature has mainly looked at the impacts of the automation process associated with computers. We argue that complex software is more likely to be already replacing the use of routine-cognitive and analytical tasks, which are typically performed by more skilled workers.

Our firm-level findings show several interesting patterns for Chile. First, the level of the managerial human capital is an important driver of the adoption of advanced technologies. In particular, younger, more experienced and more formally educated managers working in younger and larger firms are more likely to perceive benefits in implementing advanced technological changes. Second, in the _medium run_ , this advanced technology adoption, which is arguably 2
82 RENT CONTROL IN KUMASI, GHANA sample, the sample rent will be adjusted (multiplied by 1.6) to reduce the bias. _wA_

# E. Estimating PmOm With Kumasi Survey Data

As noted above, the rent that households would pay if they were at their equilibrium demand at market prices (PmQm) can also be estimated from the household survey. Table 5.5 presents the estimated coefficients from the expenditure regression estimated using the sample of "uncontrolled" renters. Only households in the tenement and indigenous sectors are included. Households and (especially) units in the government and high cost sectors are so different from the rest of the sample that they were omitted.-71 The dependent variable is gross rent, adjusted as described above (multiplied by 1.6).

The demand results are reasonable, with an R-squared of 0.18. The estimated consumption elasticity is 0.28. This is a low estimate compared to others from the Malpezzi and Mayo results above.

The relationship between rents and length of tenure is strong; transformation of the log-log model shows rents falling about 15 percent per year in the first few years of tenure, and around 1 percent per year at 20 years. The total discount at 20 years and beyond is about 40 percent. There have not been many studies of this discount in developing countries; this i. high but within range of estimates of length of tenure discounts for U.S. cities found by Malpezzi, Ozanne and Thibodeau (1981). Household size is a weec demand determinant.

- j6/ See Malpezzi (1;.o6) pp. 129-139 and Fallis and Smith (1984) for more detailed justification.

- l! In general, if we know the "true" model a priori and have all the data necessary to implement it, we could gain valuable information from the omitted government and high cost units. However neither condition is satisfied, and dropping these sectors as unrepresentative is, we believe, the conservative procedure.