rafmacalaba/datause-encoder-data huggingface dataset:
|**Table 10. Sector Imports as a Percent o**|**f Total Import**|**s of the Fed**|**eral Okrug**|||||Sector|
|---|---|---|---|---|---|---|---|---|
|**Sector**<sup>**b/**</sup>|Northwest|Central|South|Volga|Urals|Siberia|Far East|total|
|Railway transportation|0.1|0.1|0.1|0.1|0.2|0.2|0.1|0.1|
|Truck transportation|0.2|0.2|0.3|0.4|0.6|0.4|0.3|0.3|
|Pipelines transportation|||||||||
|Maritime transportation|||||||||
|Air transportation|0.2|0.2|0.3|0.3|0.3|0.3|0.3|0.2|
|Other transportation|0.1|0.1|0.1|0.1|0.2|0.1|0.1|0.1|
|Telecommunications|0.4|0.5|0.6|0.8|0.9|0.8|0.6|0.6|
|Science & science servicing|0.0|0.0|0.0|0.0|0.0|0.0|0.0|0.0|
|Financial services|0.9|1.0|1.2|1.6|1.9|1.8|1.5|1.3|
|Ferrous metallurgy|2.5|2.9|5.3|3.7|2.3|1.8|2.2|3.0|
|Non-ferrous metallurgy|1.9|1.9|2.7|2.5|2.1|1.1|1.2|2.0|
|Chemical & oil-chemical industry|7.1|8.4|5.8|7.5|6.9|13.0|8.4|8.1|
|Mechanical engineering & metal-working|33.3|33.1|22.6|19.2|22.7|12.6|25.8|27.4|
|Timber & woodworking & pulp & paper industry|3.0|3.6|2.7|0.7|0.6|0.4|0.8|2.4|
|Construction materials industry|1.7|2.2|2.0|1.9|1.3|2.7|1.1|2.0|
|Food industry|18.0|13.4|10.3|8.8|7.2|10.1|10.0|12.1|
|Other industries|0.4|0.4|0.8|0.9|0.8|0.9|0.7|0.6|
|Public services, culture and arts|0.6|0.6|0.8|1.0|1.1|1.1|0.9|0.8|
|Agriculture & forestry|2.1|2.2|3.8|3.4|2.2|3.6|3.3|2.6|
|Coalmining|0.3|0.2|0.3|0.4|0.6|1.1|0.5|0.4|
|Housing and communal services|2.0|2.4|3.0|3.4|3.2|3.8|3.1|2.8|
|Construction|5.6|4.0|7.8|9.1|15.5|7.8|9.9|6.9|
|Electric industry|0.2|0.1|0.2|0.3|0.3|0.4|0.3|0.2|
|Gas|0.1|0.1|0.1|0.1|0.2|0.1|0.1|0.<br>1|
|Crude oil extraction|0.7|0.4|1.1|2.8|0.9|2.0|1.0|1.0|
|Oil refining and processing|2.0|1.8|3.1|4.0|4.0|3.7|2.7|2.6|
|Other goods-producing sectors|0.9|0.9|1.3|1.8|2.2|1.8|1.4|1.3|
|Post|0.0|0.0|0.1|0.1|0.1|0.1|0.1|0.<br>1|
|Wholesale and retail trade|0.6|0.6|0.9|1.1|1.6|1.2|1.0|0.8|
|Textiles and apparel|14.9|18.7|22.6|23.9|20.3|27.1|22.6|20.2|
|Okrug Total:|12.8|42.9|8.5|13.7|9.9|8.1|4.1||

44
_Brazilian spatial labor dynamics Page 25_

|Dependent Variable:<br>Delta ln Employment|2SLS Est.|2SLS SE|Spatial GMM<br>Est.<br>(Cutoff = 0.5)|Spatial GMM<br>SE<br>(Cutoff = 0.5)|
|---|---|---|---|---|
|Intercept|-1.0038159|.14846142|-.97731119|.21782738|
|ln Wage in 1991|.19207975|.01553089|.190244|.02302395|
|ln 5 to 15 over 15 to 55 yrs Ratio|.25067678|.03711903|.24860755|.0545722|
|Proportion of Natives in 1991|.292077|.04174566|.31104589|.06760336|
|Delta ln Market Potential|.2035026|.02778313|.19855203|.04571589|
|ln Teacher Qualification in 1991|-.00699189|.00239773|-.00710868|.00376014|
|Homicides in 1991|-9.7408304|4.5089288|-13.952994|12.869347|
|Employment in Farming in 1991|-.55168569|.17153628|-.62525272|.27117524|
|Bank Dummy|-.0029771|.00978021|.00085738|.01357927|
|ln Population in 1991|-.02653262|.00623792|-.02801059|.009894|
|Mean Temperature|-.00246354|.00267179|-.00177658|.00416755|
|Total Rainfall|3.313e-06|.00001244|7.357e-06|.00002025|
|Rainfall - 1o Princ. Component|.00715906|.00194123|.00712434|.0032946|
|Rainfall - 3o Princ. Component|.01638063|.0044276|.01515498|.00688489|
|Employment rate in 1991|.17582282|.14548762|.21597567|.23001887|
|crit. fn. test of overid. restrictions|----|----|6.5507803|6.5507803|
|Dependent Variable:<br>Delta ln Employment|Spatial GMM<br>Est.<br>(Cutoff = 1)|Spatial GMM<br>SE<br>(Cutoff = 1|Spatial GMM<br>Est.<br>(Cutoff = 2)|Spatial GMM<br>SE<br>(Cutoff = 2)|
|Intercept|-.94565964|.24317868|-.8953951|.27096564|
|ln Wage in 1991|.1860382|.02520692|.17956887|.02802359|
|ln 5 to 15 over 15 to 55 yrs Ratio|<br>.2456395|.06085758|.2379445|.06769622|
|Proportion of Natives in 1991|.31289083|.07724686|.30829117|.08909906|
|Delta ln Market Potential|.19815785|.05295998|.19621347|.06306989|
|ln Teacher Qualification in 1991|-.00740787|.00443293|-.00709898|.00504883|
|Homicides in 1991|-18.404268|18.498964|-26.86664|28.508017|
|Employment in Farming in 1991|-.6742841|.31386852|-.72451919|.35913906|
|Bank Dummy|.00197269|.0137091|.00300001|.01441328|
|ln Population in 1991|-.02758414|.01119957|-.02459399|.01372423|
|Mean Temperature|-.00145903|.00495593|-.00197288|.00596594|
|Total Rainfall|.00001497|.00002414|.00002119|.00002897|
|Rainfall - 1o Princ. Component|.00662112|.00376597|.00617786|.00420715|
|Rainfall - 3o Princ. Component|.01389925|.00844409|.01335848|.009971|
|Employment rate in 1991|.23755644|.25803682|.25136152|.28428775|
|crit. fn. test of overid. restrictions|5.2505856|5.2505856|4.0939112|4.0939112|
**_Figure 8.  Market Access Overall Trade Restrictiveness Index, by exporters and markets, 2008_**

<!-- Start of picture text --> Percent<br>70<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>High-income East Asia & Europe & Latin America Middle East & South Asia Sub-Saharan<br>countries Pacific Central Asia & Caribbean North Africa Africa<br>Market<br>High-income countries East Asia & Pacific<br>Europe & Central Asia Latin America & Caribbean<br>Middle East & North Africa South Asia<br><!-- End of picture text --> _Source_ : World Bank and UNCTAD staff estimates.

# **The pervasiveness of NTMs is compounded by relatively poor regional trade logistic**

**performance.** Data on the performance of logistics services and on the internal costs associated with shipping goods from the factory gate to the port, and from ports to retail outlets suggest that traders confront significant hurdles in the region, with only the UAE being among the world’s better performers. The _Doing Business_ “cost of trading” data indicate that the costs associated with completing the procedures to export or import a 20-foot container (document and administrative fees for customs clearance and technical control, terminal handling charges and inland transport) remain high in the region (Figure 9).<sup>16</sup> Only Bahrain, Egypt, Qatar, Saudi Arabia, and the UAE were among the 30 top performers in 2009.   Similarly, the Logistics Performance Index (LPI) reveals a great deal of variance and significant performance bottlenecks within many Arab countries (Figure 10).<sup>17</sup> Performance in the mostly high income Gulf states is noticeably stronger, but still well below their income group average. The standout performer is the UAE, ranked 24th in the world in the 2010 LPI, with a score comparable to that of Korea.

> 16 The cost measure does not include tariffs or trade taxes. Only official costs are recorded. Inland transport costs are based on distance to the shipping port. The methodology, surveys and data are available at <u>http://www.doingbusiness.org.</u>

> 17 The Logistics Performance Index (LPI) is based on a worldwide survey of operators on the ground (global freight forwarders and express carriers), providing feedback on the logistics “friendliness” of the countries in which they operate and those with which they trade. The methodology, surveys and data are available at <u>http://www.worldbank.org/lpi.</u>

16
|With SFD&DFD<br>variables<br>(8)<br>0.97_∗∗∗_<br>(0.31)<br>0.82_∗∗∗_<br>(0.20)<br>-3.67_∗∗∗_<br>(0.86)<br>-2.67_∗∗∗_<br>(0.79)<br>-0.06<br>(0.80)<br>0.16<br>(0.43)<br>66352<br>ry-pair fxed effects<br>ation. FV: fnancial<br>|
|---|
|TANG<br>D X DFD<br>(7)<br>0.91_∗∗∗_<br>(0.29)<br>0.85_∗∗∗_<br>(0.20)<br>-3.82_∗∗∗_<br>(0.88)<br>-2.41_∗∗∗_<br>(0.75)<br>-1.90_∗_<br>(1.08)<br>33618<br>e-invariant count<br>ource. D: Destin<br>cial development.|
|_sector_<br>ED<br>with SF<br>(6)<br>0.83_∗∗∗_<br>(0.30)<br>0.69_∗∗∗_<br>(0.21)<br>-3.80_∗∗∗_<br>(0.82)<br>-2.72_∗∗∗_<br>(0.77)<br>0.71_∗∗_<br>(0.34)<br>33618<br> (1)-(7). Tim<br> quality. S: S<br>untries’ fnan|
|_feld FDI, by_<br>Both<br>FV measures<br>(5)<br>0.93_∗∗∗_<br>(0.30)<br>0.86_∗∗∗_<br>(0.21)<br>-3.64_∗∗∗_<br>(0.85)<br>-2.65_∗∗∗_<br>(0.77)<br>33618<br>ded in regressions <br>capita, institutional <br>urce/destination co|
|_Volume of bilateral green_<br>ED<br>TANG<br>mature frms<br>FV measure<br>(3)<br>(4)<br>0.64_∗_<br>(0.37)<br>-0.11<br>(0.36)<br>-4.84_∗∗∗_<br>(0.87)<br>-4.14_∗∗∗_<br>(0.88)<br>30072<br>33618<br>-pair and sector fxed effects are inclu<br>riables on both sides: GDP, GDP per <br>asure of asset tangibility. SFD/DFD: so|
|ED<br>young frms<br>(2)<br>0.64_∗∗∗_<br>(0.18)<br>0.93_∗∗∗_<br>(0.13)<br>33618<br>me-varying country<br>ollowing control va<br>sector-specifc me|
|Without two<br>outlying sectors<br>(1)<br>2.13_∗∗∗_<br>(0.51)<br>1.33_∗∗∗_<br>(0.33)<br>25575<br>rs in parentheses. Ti<br>n (8), as well as the f<br>ternal fnance. TANG:|
|S. ln(credit/GDP) X ED<br>D. ln(credit/GDP) X ED<br>S. ln(credit/GDP) X ED_young<br>D. ln(credit/GDP) X ED_young<br>S. ln(credit/GDP) X ED_mature<br>D. ln(credit/GDP) X ED_mature<br>S. ln(credit/GDP) X TANG<br>D. ln(credit/GDP) X TANG<br>S. ln(credit/GDP) X D. ln(credit/GDP) X ED<br>S. ln(credit/GDP) X D. ln(credit/GDP) X TANG<br>S. ln(credit/GDP)<br>D. ln(credit/GDP)<br>Observations<br>_∗∗∗_p_<_0.01 _∗∗_p_<_0.05 _∗_p_<_0.10. Cluster-robust standard erro<br>and time-varying sector fxed effects are included in regressio<br>vulnerability. ED: sector-specifc measure of dependence on ex|

30
<!-- Start of picture text --> Effect on GDP of a shock to government spending of 1 p.p. of GDP<br>cumulative response at 12 quarters (source: Perotti, 2005)<br>4<br>1960-1980<br>3<br>1980-2001<br>2<br>1<br>0<br>-1<br>-2<br>-3<br>Australia Canada Germany United Kingdom United States<br>Effect on GDP of a cut in net taxes of 1 p.p. of GDP<br>cumulative response at 12 quarters (source: Perotti, 2005)<br>3<br>1960-1980<br>2<br>1980-2001<br>1<br>0<br>-1<br>-2<br>-3<br>Australia Canada Germany United Kingdom United States<br><!-- End of picture text -->

**Studies drawing on aggregate dynamic macro models conclude that fiscal multipliers are in the range of 0.3 to 1.2 percent, and that expenditure measures appear to have a larger effect than tax measures** (Hemming et al 2002, Botman 2006). Other studies find that government investment has the largest impact on economic activity and inflation. However, the size of the estimated multipliers depends on assumptions about, among other things, the monetary regime, labor supply elasticities and liquidity constraints (IMF, 2008).

# **3. METHODOLOGY**

**This paper focuses on two measures: a general government tax cut and a general government expenditure increase** . The expenditure variable is defined as total purchases of goods and services, meaning government consumption plus government investment. The revenue variable is defined as total tax revenues minus transfers.

**The traditional approach in the literature consists in estimating impulse reaction functions using a vector autoregressive (VAR) model** (see for example Blanchard and Perotti, 1999 or Bernanke and Mihov, 1998 for monetary policy). Fiscal multipliers are than computed summing the first four, eight or 12 periods of the reaction functions. The basic reduced VAR specification is as follows: _Z t_ = Γ ( _L_ ) _Z t_ − 1 + _ut_ )1( where _Z t_ is a three' dimensional vector ( _Z t_ = [ _Yt_ , _Et_ , _Rt_ ] ) in the logarithms of quarterly observations for government consumption, government revenues and private consumption.

4
While PNG continues to battle a high stunting rate, it also faces emerging non-communicable diseases. As evidence has shown, an adult is more likely to develop non-communicable diseases if he/she was stunted as a child. The body’s ability to metabolize food is being programmed in the first 1000 days from conception and disruption to this process contributes to obesity and diabetes later in life (Stuart Gillespie and Lawrence Haddad 2001). This will not only pose a huge financial burden to families, but also the public health financing schemes.

Further analytics are required to better understand the causes for undernutrition and over-nutrition and the effects of various interventions. The quality of HIES data collection methods, particularly the questionnaire design, can be further strengthened to make it a more useful tool in identifying areas for health policy interventions and reform. To the extent possible, regular nutrition surveys to monitor nutrition status add tremendous value to understand the progress of improving nutrition outcomes and the causal links. Additional analytical work that can further shed light on combating the undernutrition issue includes: investigating the prevalence of deficiencies of micronutrients (vitamin A, zinc, iron, and iodine) in the subnational population; and obtaining a better understanding of the nutrition inventions to date in PNG and analysis of the lessons learned. These efforts will help in scaling up effective interventions using various platforms and linking child nutrition with cognitive development for school readiness and beyond.

To move toward more committed actions, it is critical to improve the political environment, aligning multiple actors, and advancing policies and legislation. The government has made some progress. The National Nutrition Policy was recently endorsed by a number of departments in addition to the National Department of Health in early 2015, highlighting the political commitment of multisectoral interventions to improve nutritional outcomes in the country. However, a much stronger political commitment along with adequate financing are required to ensure the successful implementation of the policy. Monitoring and evaluation of nutritional programs are necessary to gather the latest evidence on the effective and efficient ways to improve nutrition across different regions in PNG.

13
where _Topij_ is a dummy reflecting top innovating firms. Other variables are defined as equation 1. We find evidence that the top innovating firms are somewhat more insulated from the effects of the sanctions (see columns (1) to (3) of Table 7). The estimated coefficient _α_ is significant and positive for total patents at both extensive and intensive margins and for high-tech patents at intensive margins only. Among firms patenting in a given year, U.S. sanctions are not as effective at curbing top innovators’ overall and high-tech patenting. However, they appear similarly effective in deterring international patents, regardless of the firm’s patenting capacity.

We further explore whether firms in sectors close to the global knowledge frontier or more reliant on indigenous innovations are less affected by the U.S. sanctions. To measure the distance to the knowledge frontier, we follow the approach of Akcigit et al. 2024, computing the ratio of triadic patents filed by Chinese firms to the total triadic patents filed by either Chinese or U.S. firms in each 2-digit ISIC sector<sup>16</sup> . We examine sector-level indigenous innovation through the lens of cross-border technology sourcing and adoptions, using several measures from previous literature (Archibugi and Michie 1995; Bian et al. 2023), such as learning from prior technology (Jaffe et al. 1993; Thompson 2006 ), direct adoption (Eaton and Kortum 1999), and direct collaboration (Giuliani et al. 2016; S. P. Kerr and W. R. Kerr 2018).

Patent citations are a well-established metric for assessing knowledge spillovers and sourcing (see Keller 2004 and Bloom et al. 2019 for review). A larger share of citations to foreign patents suggests a significant reliance on foreign “prior art”. We measure the importance of domestic knowledge sourcing as the share of citations made to Chinese patents in each 2-digit ISIC sector. To assess the direct adoption of foreign knowledge, we track a patent’s priority number and count the number of patents previously granted in a foreign patent office but reapplied for in the domestic office at each 2-digit ISIC sector, which could indi-

> 16Patents in PATSTAT are assigned with IPC code. We first use the concordance table provided by PATSTAT to convert each IPC code into NACE version 2, and then use the concordance table in https://unstats.un.org/unsd/classifications/Econ, to covert NACE version 2 into ISIC revision 4. Patents used to compute knowledge distance are then classified into 2 digit ISIC sector.

19
<!-- Start of picture text --> in the richest 60 percent. The gap was largest in East Asia and the Pacific, where those<br>in the poorer group were twice as likely to borrow for this reason, but absent in Latin<br>America and the Caribbean.<br>Borrowing for education and borrowing to start, operate, or expand a business were<br>each reported by 8 percent of adults in developing economies. Sub-Saharan Africa had<br>the largest shares of adults reporting borrowing for both these purposes, at around 12<br>percent for each.<br>In high-income OECD economies about 5 percent or fewer adults reported having borrowed<br>in the past 12 months for health, for education, or to start, operate, or expand a business.<br>Globally, about 21 percent of adults reported borrowing for a reason other than these<br>purposes—28 percent of adults in high-income OECD economies and 20 percent in de-<br>veloping economies. This may include borrowing for weddings or funerals or for a large<br>purchase. 10<br>Saving or borrowing for business?<br>When people make investments they have two basic ways to finance them: they can save<br>the money up front, or they can borrow the money and then make periodic payments<br>to pay off their credit. Data from the 2014 Global Findex survey shed some light on how<br>people around the world finance investments in business.<br>Globally, 17 percent of adults around the world reported having either saved or borrowed<br>in the past 12 months to start, operate, or expand a business. And of those who did, the<br>overwhelming majority reported that they had saved: 79 percent saved—with 59 percent<br>only saving and 20 percent both saving and borrowing—and 21 percent only borrowed.<br>Business owners were more likely than the FIGURE 3.12<br>How business owners finance investments in business<br>general population to report having saved<br>Business owners using financing method in the past year (%), 2014<br>or borrowed for business purposes—almost<br>half reported doing so. But again across 54 55<br>all regions, even the majority of this group 44 42<br>reported that they had saved: 82 percent 38 Saving<br>32<br>saved—with 54 percent only saving and 28<br>24<br>percent both saving and borrowing—and 18<br>percent only borrowed (figure 3.12). This Both savingand borrowing<br>result is in line with the finding of research<br>Borrowing<br>that in the United States entrepreneurs<br>East Asia Europe High-income Latin Middle South Sub-Saharan<br>have a higher savings rate than the general & Pacific & Central OECD America & East Asia Africa<br>Asia economies Caribbean<br>population, contrary to the expectation Source: Global Findex database.<br>that they would be likely to take financial<br>risks and pay more for credit. 11 But what<br>these numbers might also reflect in part<br>is that people might save for many years<br>in anticipation of starting a business, then<br>borrow only once the business is established.<br>THE GLOBAL FINDEX DATABASE 53<br><!-- End of picture text -->
following a similar path. In the most prominent example to date, China has invested close to $9 billion in the Democratic Republic of Congo, and it is emerging as one of the largest nonOECD/DAC bilateral aid donors. The increasing in trade and aid based on convergence of interests is matched by an increase in institutional fora and platforms with greater engagement between African and Chinese policymakers across a wide variety of issues. As China’s ascent continues, its relationship with Africa can only grow.

<!-- Start of picture text --> CHART 2: CURRENT ACCOUNT BALANCES:<br>CHINA VS SSA ($ US BILLION)<br>500<br>400<br>300<br>200<br>100<br>0<br>-100<br>Africa: Sub-Sahara China<br>198019821984198619881990199219941996199820002002200420062008<br><!-- End of picture text --> <!-- Start of picture text --> CHART 3: AVERAGE INFLATION RATES:<br>CHINA VS SSA (%)<br>45<br>40<br>35<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>-5<br>SSA China<br>199519961997199819992000200120022003200420052006200720082009<br><!-- End of picture text --> 10
using national statistical sources. The performance payment is divided equally among the ten tracers, with four percentage points assigned to each, totaling up to 40 percent. If the target is met, the province receives the full 4 percent of the capita for that tracer. If it does not meet the target, it receives nothing for that tracer.<sup>6</sup> Payments are made every four months.

# **2.3. Payment to Clinics**

Each province uses these resources to pay clinics for priority maternal and infant health services on a fee-for-service basis. The 80 services included are defined at the national level, with the provincial health authority determining the prices of the services. Only clinics affiliated with the program can be paid and only for services included in the package provided to persons enrolled in the program. The program includes an intensive process for auditing and verifying clinic records to ascertain the validity of payments made.

The services in the nomenclature package were chosen based on their priority in terms of maximizing the probability of good maternal and child health outcomes. Services include preventive and diagnostic visits for pregnant women, new mothers and children, delivery care, laboratory analyses and imaging, and health care promotion (table 2). Some services include visits such as prenatal and well-baby care; other clinical services provided during these visits, such as vaccines, diagnostic tests, and reproductive health counseling included in the package, are meant to represent higher quality of care. Hence, clinics are paid more for providing higher-quality care to more beneficiaries.

Plan Nacer resources supplement the regular operating budget of the clinic. General guidelines for the use of resources by providers are set at a national level, and provinces are allowed to impose additional restrictions for service providers in their jurisdictions. However, within these guidelines, resources may be used at the discretion of the provider to improve the quality of health services. Specifically, expenditures permitted by the program include medical and office supplies, maintenance (infrastructure), investments (infrastructure and medical equipment), agreements for works and services (staff recruitment), and staff incentives.<sup>7</sup>

> 6. In May 2008, the "all or nothing" scheme was modified to a sliding scale with four thresholds rather than one (Argentina. Ministry of Health. 2008b).

> 7. For more information on the structure and operation of the program, see Argentina, Ministry of Health 2008b.

7