rafmacalaba/datause-encoder-data huggingface dataset:
15 It is also useful to compare the TRI and WRI results for the 19 focus countries to the TRI and WRI estimates for other developing country regions, which are reported in Lloyd, Croser and Anderson (2010). The 19 African focus countries had the most welfare reducing policies over time, and generally the most trade-distorting. All three regions have shown a trend towards less trade and welfare reducing agricultural policies in recent years, however (Figure 4).

# **_Policy instrument results_**

We now turn to the national decompositions of the TRI and WRI to the policy instrument level. Figure 5 provides a summary of the estimates of the contribution to the weighted average WRI series for the 19 African focus countries of four different border measures: taxes and subsidies on both imports and exports. The figure demonstrates the very substantial role that export taxes have played in the reduction of welfare in the region. On average, more than half the welfare reductions have come from anti-agricultural export taxing policies over the period studied. Notwithstanding their significant distortionary contribution, export taxes have also been the area in which there has been most reform in recent decades. The contribution of export taxes to the reduction in the WRI over the period 1985–89 to 2000–04 is 93 percent. Import taxes reduced the overall WRI by 34 percent; while there were offsetting increases in the contribution of export subsidies (13 percent) and import subsidies (15 percent) to the WRI. The contributions to TRI and WRI estimates for the 19 African countries from domestic distortions are small, never accounting for more than 2 percent of the overall regional TRI or WRI.

# **_Commodity TRI and WRI results_**

The TRI and WRI estimates for individual regional commodity markets provide a different perspective on the level of distortion in the 19 focus countries over the period under analysis. Table 7 reports the five-year average WRI estimates for the focus region for individual commodity markets. The table reveals considerable diversity in the distortions in different commodity markets. Fruit and vegetable commodity markets, which tend to have a high share of nontradable production, have low WRI estimates on average, whereas traded commodities such as tropical crops,
# **Policy Research Working Paper Series**

|**Title**|**Author**|**Date**|**Contact**<br>**for paper**|
|---|---|---|---|
|WPS2340 Currency Substitution in Latin<br>America: Lessons from the 1990s|Pere Gomis-Porqueras<br>Carlos Serrano<br>Alejandro Somuanp|May 2000|M. Puentes<br>39621|
|WPS2341 The Tyranny of Concepts: CUDIE<br>(Cumulated, Depreciated Investment<br>Effort) Is_Not_Capital|Lant Pritchett|May 2000|R. Widuri|
|WPS2342 What Can We Learn about Country<br>Performance from Conditional<br>Comparisons across Countries?|Martin Ravallion|May 2000|P. Sader<br>33902|
|WPS2343 Ownership and Performance of<br>Lithuanian Enterprises|David A. Grigorian|May 2000|D. Brown<br>33542|
|WPS2344 Designing Direct Subsidies for<br>Water and Sanitation Services:<br>Panama-A Case Study|Vivien Foster<br>Andres G6mez-Lobo<br>Jonathan Halpern|May 2000|S. Delgado<br>37840|
|WPS2345 Information and Modeling Issues in<br>Designing Water and Sanitation<br>Subsidy Schemes|Andres G6mez-Lobo<br>Vivien Foster<br>Jonathan Halpern|May 2000|S. Delgado<br>37840|
|WPS2346 The Middle Class Consensus and<br>Economic Development|William Easterly|May 2000|K. Labrie<br>31001|
|WPS2347 Terror as a Bargaining Instrument:<br>A Case Study of Dowry Violence in<br>Rural India|Francis Bloch<br>Vijayendra Rao|May 2000|P. Sader<br>33902|
|WPS2348 Taxing Issues with Privatization:<br>A Checklist|Jack M. Mintz<br>Duanjie Chen<br>Evangelia Zorotheos|May 2000|G. Chenet-Smith<br>36370|
|WPS2349 Trade, Foreign Direct Investment,<br>and International Technology<br>Transfer: A Survey|Kamal Saggi|May 2000|R. Bonfield<br>31248|
|WPS2350 Multilateral Trade Liberalization and<br>Political Disintegration: Implications<br>for the Evolution of Free Trade Areas<br>and Customs Unions|Maurice Schiff|May 2000|L. Tabada<br>36896|
|WPS2351 Environmental Policy and Time<br>Consistency: Emissions Taxes<br>and Emissions Trading|Peter W. Kennedy<br>Benoit Laplante|May 2000|Y. D'Souza<br>31449|
<!-- Start of picture text --> Transparency and Governance Index<br>eee<br>Nee eS*§<br>TT 3. 3?<br>Setha Act 22 3)<br>QS(iC27 2222<br>27<br>OO 25<br>TS<br>SO 2<br>24<br>Oi_— 24<br>23<br>23<br>TT22<br>ihieS 7120 27<br>CT 20<br> — ir<br>bi?a TT 15 17<br>Tenahe|S) a a1 15<br>SiLanke mp 11<br>SaudiArable 1D<br>aoa<br>10 15 20 25 30 35<br><!-- End of picture text -->

<!-- Start of picture text --> 90<br>° Pe Kew<br>80 / Botewane e . \\<br>0 |\* ° e Australia s 7|<br>i Namibia /<br>e ff<br>g= 60 “<br>S =<br>i -<br>i= 50 e .<br>a 2<br>o :<br>2 40<br>a a<br>$re)3 30<br>5 - ys dasdxt 23271<br>* 20 R= 0.1381<br>*<br>10<br>0<br>25 30 35<br>4 am<br>Transparency and Governance Index<br><!-- End of picture text -->
continuously augment the stock of knowledge and ensure a sufficient flow of innovations (see Table 3).

**Table 3 – R & D Expenditures and Sectoral Distribution in 2004**

|||Share of R&Dby Sect<br>|or<br>|GERD as percent of<br>|
|---|---|---|---|---|
|Country|Industry|Higher Education|Government|GDP|
|Finland|70.1|19.8|9.5|3.51|
|Japan|75.2|13.4|9.5|3.13|
|Korea|76.7|9.9|12.1|2.85|
|United States|70.1|13.6|12.2|2.68|
|EU-25|63.3|22.1|13.4|1.81|
|China|66.8|10.2|23.0|1.23|

Source: OECD Science, Technology and Industry Outlook 2006.

Governments have tended to shoulder more of the financing burden for basic research in universities and research institutes which adds to the pool of scientific knowledge<sup>29</sup> although they do support downstream and applied research by corporations as well. In the majority of cases, resources from the public sector (including for university based research) account for between 20 and 40 percent of spending on R&D (Table 3). The balance comes from the private sector, which typically invests more in applied research and in the development of scientific findings.

This division of responsibilities for R&D points towards the vital role which the business sector and especially, large companies play in the activity of commercialization and marketing. The economic benefit which is derived from innovation by a creative workforce is only fully realized when an innovation acquires a commercial form and value. As I noted earlier, the chain extending from the garnering of knowledge by creative people to the actual marketing of an innovative product or service, which embodies that knowledge, is a lengthy one. It can also entail a significant expenditure of time and resources.

> 29 Some of the key research underlying innovation by Pharmaceutical industry in the U.S. was done in public labs or with government fundings.

11
in Treatment 1, households received daily text message for approximately two months with information on the level of outdoor air pollution near their house. This information was based on the readings from the nearest PurpleAir monitor to their house from 8am10am that day and was sent at 10am every day. We document, and report to the household, that the pollution level from 8am-10am was positively correlated with the pollution level for the rest of the day and could be used to inform their expectations about those levels.

_Treatment 3 (Outdoor and Indoor pollution) -_ In addition to the leaflet, households received the same daily text message as Treatment 2 for approximately two months. In the text message, they also received the average level of indoor air pollution over the last 24 hours in their house. To provide this information, households in treatment 3 all received an indoor PurpleAir monitor that recorded the level of PM2 _._ 5 in their house in real-time. These devices also indicate the quality of air in real-time using a color-scale from green (good) to red (bad). If the household did not consent to host an indoor air pollution monitor, the surveyor ended the survey and followed the same random selection process to select another household. Installation occurred the week following the survey and monitors were installed in a primary living space that was not the kitchen.

The end-line survey was conducted two months later, in late May and early June. At this time, a hundred percent of the surveyed households at baseline were revisited. At this time, all households who completed both surveys received a payment for participation. The size of the payment varied depending on the treatment. Households in the Control group and Treatment 1 received 30 GEL, while the ones in Treatment 2 received 50 GEL and the ones in Treatment 3 received 70 GEL.<sup>8</sup> The survey measured outcomes to assess the effectiveness of the embedded information intervention, such as self-reported health symptoms.

# **2.3 Balance test**

We show in Table A1 that treatments are generally balanced across observables using data from the baseline survey. We report the difference in means between each of the treatment groups and

> 8At the time of the payments, 1 GEL was approximately 0.38USD.

8
simple, as it requires only information on import levels in the current year relative to imports in a 3-year moving-average baseline. The second would be much more complex because it requires much more difficult-to-obtain information on whether individual households are net buyers or net sellers of the products in question. An important question is therefore how application of the measure in line with the proposed WTO rules would affect poverty in developing countries and globally.

While many studies (e.g. Montemayor 2007; Grant and Meilke 2009; Hertel, Martin and Leister 2010) examine the implications of the SSM proposals for aggregate variables such as market prices and farm incomes, almost no analysis is available at the household level needed to assess the implications of the SSM for its intended objectives of improving food security, livelihood security and rural development. For an excellent overview of related issues of the implementation of SSM policies and a review of many quantitative and qualitative studies on the subject, see Grant and Meilke (2011).

This paper uses data at the household level to assess the implications of the volume-based SSM for household welfare, and particularly for the number of people who fall below the internationally standard poverty line of $1.25 per day (Ravallion, Chen and Sangraula 2009), and hence face increased risks to their food and livelihood security. In the following sections of this paper, we develop a methodology to assess the frequency with which the volume-based safeguard might be applied, and how its effects might be assessed. After a short discussion of the data available for the analysis, we present poverty estimates of our simulations for a set of individual developing countries as well as for the world as a whole.

# **Methodology**

The proposed SSM involves both a price-based and a quantity-based measure. The price-based measure (P-SSM) is much simpler to use than the Q-SSM, as it can be invoked whenever the price of a shipment falls below a trigger level based on a moving average of import prices from all sources (Hertel, Martin and Leister 2010). As noted by Martin and Anderson (2011) and Anderson, Ivanic and Martin (2013), such price-based measures are likely to be attractive for individual developing countries—and have been widely used in the industrial countries in the past. They can stabilize domestic prices in individual, small countries relative to the situation without such intervention. One concern with the shipment-by-shipment nature of the proposed 3
# **VI.    How Did the Firms Rate the Technical Skills of Locally Educated MBAs?**

## **Figure 2**

<!-- Start of picture text --> MBA Survey Question 6A: How would you rate<br>the technical skills of locally educated MBAs?<br>4%<br>8%<br>30%<br>39%<br>LACKING (%) INADEQUATE (%)<br>ADEQUATE (%) GOOD (%)<br><!-- End of picture text --> As Figure 2 shows, 69% of the survey respondents found the technical skills of the locally trained MBAs to be either adequate or good.

At the regional level, three regions stand out. First, 25% of respondents in Africa found the technical skills of business graduates to be lacking or inadequate. Considering the fact that for the entire survey sample of firms only 12% of the firms found the technical skills of business graduates lacking or inadequate, the African statistics imply a particular problem in the quality of technical training of African business school graduates. The other cases that are noteworthy are the South Asian results, in which 21% of the respondents were dissatisfied with the quality of technical training, and the Middle Eastern results in which 17% of respondents found the quality of technical skills inadequate.

On the other end of the scale, firms from East Asia, Europe and Latin America were satisfied with the quality of technical training imparted by local business schools. Specifically, 72% of the East Asian respondents, 70% of the European respondents and 80% of the Latin American respondents rated the technical training of local MBA graduates to be either adequate or good.

An analysis of the responses across World Bank income categories demonstrates that the countries making up Category I (the lowest income category) are the least satisfied with the technical skills of local MBAs: 20% of responding firms from Category I found the technical skills of locally educated MBAs to be lacking or inadequate, more than those of 12
<!-- Start of picture text --> Health . Hospitals<br>, a ae inal” e Py aaa e: ‘ "e @<br>PE Eo a i init e° e @ o%%<br>e2".itlyorsh18: ee.PoP 27%S ocr@e-.cee aehaesi é, eeL :#.; "if @ -@lhexee©.@ ©Ste we@ / bd 4 ¥. >100<br>E55 MeeeSs 4% oe ee @ 8<br>4.8% Be AS oe Se "5 Pe es e °m°*.°’- & Ge ee @ e ? al 80 8<br>+e, TS*e owesoe a e °cy “oe @e @e° iadeX e ?.@ "e a 23<br>ées*ApeSN ¢Yr ‘Ssoe; P eevee ©éoe 40 553<br>Re .° 2 §<br>e ° =<br>e °.<br>Education . Substations is<br>Be eeeke, “ee SER ee, Ee Eerie hiie oe - . . ry >100 _<br>feat : ae fee Bey, +2) ¢ e 60 2<br>pg . 20 $<br>‘ E<br>phe e<br>.. 0<br>Number of households (x1,000) % 7 Number of households (x1,000)<br>*5/1 @50025 200400 .x *5/1 @50025 Sic200 ‘<br>* 10 @ 100 * 10 @ 100<br><!-- End of picture text -->
**Figure 2: Positive Perceptions of changes in the quality of health and education services in**

<!-- Start of picture text --> the last two years in Indonesia<br>Health services Education Services<br>100 100<br>80 71.7 80 72.9<br>60 60<br>40 40<br>20.6<br>14.1<br>20 20<br>5.8 7.2<br>3.0 5.8<br>0 0<br>Better Same Worse NA Better Same Worse NA<br><!-- End of picture text --> _Source_ : GDS-2 (2006) 35
homogenous across income quintiles. The average elasticity of labor income with respect to sugar prices is 0.1 which indicates that a 10 percent increase in sugar prices will lead to an average increase in the income of Brazilian workers of about 1 percent or US$5 billion. This would lead to a 1.5 percent decline in the poverty rate.

# **References**

- [1] Baffes, John and Bruce Gardner, 2003. The transmission of world commodity prices to domestic markets under policy reforms in developing countries. Policy Reform 6(3), 159-180.

- [2] Bolling, Christine and Nydia R. Suarez, 2002. The Brazilian Sugar Industry: Recent Developments. USDA-ERS Briefings.

- [3] Guilhoto, J., A, Barros, M. Marjottoa-Maistro, and M. Istake. Mechanization process of the sugar cane harvest and its direct and indirect impact over the employment in Brazil and in its 5 macro regions. Texto de Semin ́arios, IPEUSP, N. 09/2002, 09/05/2002.

- [4] Greene, William, 2002. Econometric Analysis. Mac Millan Publishing Company.

- [5] Krivonos, Ekaterina, 2004. The impact of coffee market reforms on producer prices and price transmission. Policy Research Working Paper #3358. The World Bank.

26
_Table A 10_ : Intra-farm consistency in drought exposure reports.

# **<mark>Panel A: Ethiopia</mark>**

# **<mark>Panel B: Malawi</mark>**

|**Round**|**Crop**|**N**|**All Drought Damage **|**Round**|**Crop**|**N**<br>**All Drought Area loss**|
|---|---|---|---|---|---|---|
|ESS13|Maize|92|64%|IHPS10|Maize|91<br>90%|
||Sorghum|150|68%|IHPS13|Maize|22<br>82%|
|ESS15|Maize|333|77%|IHPS16|Maize|73<br>67%|
||Sorghum|405|89%|IHPS19|Maize|30<br>30%|
|ESS18<br>_Note: Sha_<br>|Maize<br>Sorghum<br>_re of farms wi_<br>|103<br>124<br>_th with m_<br>|50%<br>70%<br>_ore than one maize/sorghum_<br>|_Note: Shar_<br>_at least on_<br>_have drou_|_e of farms_<br>_e plot with_<br>_ght planted_|_with with more than one maize plot and_<br>_planted area loss due to drought that_<br>_area loss on every maize plot._|

_Note: Share of farms with with more than one maize/sorghum plot and at least one plot with drought damage that have damage on every maize/sorghum plot._ _Table A 11_ : Malawi - Chance-adjusted agreement coefficients for self-reported shock exposure in EAs where at least one plot recorded the respective shock.

|||**Gwet’s**||||**Obs.**|**Exp.**|||
|---|---|---|---|---|---|---|---|---|---|
|**Round**|**Shock**|**AC**|**SE**|**N Raters**|**N Subjects**|**Agreement**|**Agreement**|**LB**|**UB**|
||Drought|0.579|0.126|643|26|0.696|0.277|0.2|0.4|
|IHPS19|Flood|0.206|0.085|1057|51|0.579|0.471|0|0.2|
||Irregular Rain|0.412|0.083|1340|58|0.641|0.389|0.2|0.4|
||All shocks|0.370|0.059|1504|135|0.629|0.411|0.2|0.4|
||Drought|0.192|0.114|804|56|0.595|0.499|0|0.2|
|IHPS16|Flood|0.809|0.108|90|5|0.881|0.374|0.4|0.6|
||Irregular Rain|0.237|0.090|1000|66|0.618|0.500|0|0.2|
||All shocks|0.234|0.069|1039|127|0.617|0.500|0|0.2|
||Drought|0.501|0.097|401|25|0.662|0.324|0.2|0.4|
|IHPS13|Flood|0.326|0.090|501|31|0.633|0.457|0|0.2|
||Irregular Rain|0.432|0.080|727|47|0.648|0.380|0.2|0.4|
||All shocks|0.416|0.048|881|103|0.647|0.396|0.2|0.4|
||Drought|0.204|0.080|643|48|0.600|0.497|0|0.2|
|IHPS10|Irregular Rain|0.326|0.112|529|39|0.613|0.425|0|0.2|
||All shocks|0.224|0.076|803|87|0.605|0.491|0|0.2|

Note: Interrater reliability coefficients (Gwet's AC) for plots within the same enumeration area. Classification into benchmark interval is probabilistic, not deterministic; LB = lower boundary, UB = upper boundary; Landis and Koch (1977) benchmark scale for agreement coefficients: < 0 poor; 0-20 slight; 0.21 - 0.40 fair; 0.41 - 0.60 moderate; 0.61 - 0.80 substantial; 0.81- 1.0 almost perfect.

59
2

# **1. Introduction**

Two pressing economic issues facing the world economy are the need for fiscal consolidation in most major advanced economies and the ongoing need for more spending on infrastructure in emerging countries to support growth. While each issue has separate origins, resolving each affects the other. This asymmetric world fiscal policy adjustment has implications for global growth, trade balances and capital flows and is the focus of this paper.

Extra public borrowing by advanced economies in the aftermath of the 2009 financial crisis has meant there is less capital for investment by emerging countries. But the extra fiscal spending and borrowing has shored up growth, initially at least, in advanced economies and has meant extra demand for exports from emerging countries than would otherwise have occurred. How does the balance of these forces pan out? It is an empirical question depending on trade patterns, elasticities, multipliers and the role that extra infrastructure spending can play in emerging countries. An empirical model is therefore used to analyse the asymmetrical fiscal adjustment through a series of plausible simulations of what could be involved and the alternatives. These simulations imply some background on the size of the debt problem and the fiscal consolidation that could occur in advanced economies.

The particular the source of government debt expansion varies across countries. For some countries, a well-known example being Greece, the deterioration in fiscal position as a result of the global financial crisis came on the back of high levels of government debt that were already causing concern. Before the crisis, Greece had a level of debt to GDP of around 100 percent. Two years after the crisis, Greece’s debt had ballooned to over 125 percent of GDP<sup>2</sup> . It is expected to deteriorate further. For Ireland, the level of debt to GDP was low at around 30 percent, but increased dramatically when the Irish Government bailed out several large banks. Figure 1 shows the increase in government debt of OECD economies.

The change of fiscal policy stance from fiscal expansion in the immediate aftermath of the crisis to consolidation in coming years has fuelled another debate that has two related aspects. One is the impact of fiscal consolidation on economies that are tightening and the flow-on effects to the world economy. The other debate is how much tightening there should be and how soon, and what those effects might be. Many commentators argue that too much austerity now will simply drive the world economy back into recession and potentially bring on another financial crisis as the health of bank balance sheets and that of households have not yet fully restored. Yes, so the argument goes, fiscal austerity is needed at some stage — but, because households and businesses are busily paying down debt, now is not the time for premature tightening by governments.

> 2 On a Maastricht criteria basis as computed by the OECD Economic Outlook and taking the start of the crisis to be 2008 when Lehman Bros collapsed.
The first identification strategy is suitable for the limited number of variables which are included in the baseline (2010) data set: housing quality, livestock owned and some durable goods. For these variables, it is possible to use a difference-in-differences (DID) estimator to estimate differences in outcome trends between 2010 and 2013 across beneficiaries and non-beneficiaries: where B� is an indicator variable for beneficiary households (who received cash transfers), � is an indicator variable equal to 1 in 2013, and �� captures the impact of the cash transfers.<sup>14</sup> Standard errors are clustered at the village level. By definition, the difference-in-differences strategy controls for group fixed effects, as well as common trends between beneficiaries and non-beneficiaries.

A second identification strategy is employed for outcomes only observed in the follow-up survey. This strategy exploits a discontinuity in project beneficiary selection, in particular the variation in eligibility thresholds across villages. The PMT cut-off was set on a village-specific basis so that the project would cover 30% of the population of each village. Because the eligibility threshold varies by village, some households with similar PMT scores have different eligibility status. On that basis, we restrict the analysis to a ‘common support sample’ within a range of PMT scores that include both beneficiaries and non-beneficiaries. Figure 1 shows the spread of PMT scores across villages, and the rather wide band for which there exists a common support of beneficiaries and non-beneficiaries with similar PMT scores. While the difference in eligibility status is not random, non-beneficiary households within that band can be used to estimate counterfactual outcomes for beneficiary households with similar PMT scores. These estimates can be interpreted as Local Average Treatment Effects (LATE).

The second identification strategy is implemented by estimating a Simple Difference (SD) OLS regression on a subsample of households whose PMT scores range from the lowest village PMT threshold (���_������������) to the highest village PMT threshold (���_������������,):

> 14 With only two time periods, this specification (DID) is econometrically equivalent to using household fixed‐ effects.

12