rafmacalaba/datause-encoder-data huggingface dataset:
difficult to code, which is the reason behind the extremely high prizes – often reaching $1 million (Netflix 2009) - offered in machine learning competitions.

Third, these algorithms have been designed to be applied to large data sets with millions of observations. Although we use data from the world’s largest business plan competition, and policy makers and investors would typically have to make investment decisions based on the past performance of a more limited number of firms, our sample sizes may still make it hard to train these algorithms.

Finally, our focus has been on predicting which firms will have the best outcomes, which is an object of most interest to investors and lenders. In contrast, such predictions are usually inappropriate for a policy maker aiming to optimally allocate resources (Athey 2017), who would instead be most interested in allocating funds to firms that would benefit most from the grants, not to those firms which would be successful anyway.<sup>11</sup> But even in such cases, identifying a pool of firms that are likely to survive and grow may be a useful first step in screening applications, and policy makers may also care about offering support to the next flagship company.

> 11  See Hussam et al. (2016) for a recent application of using machine learning to predict which small entrepreneurs will have the highest returns to grants.

24
# **_4.3.3 Self-reported activity in retrospective surveys_**

Finally, we turn to the effects of the program in increasing social capital using self-reported retrospective survey measures. Table 9 reports linear probability model estimates of respondents’ answers to yes-or-no questions about whether they belonged to the specified groups. As expected the program had a large impact on SHG membership. SHG membership was about 30 percentage points higher for poor respondents and 21 points higher for non-poor respondents in LEAP communities. Both results are statistically significant.

Membership in producers groups, shown in column 2, was no different in program and control communities, which is perplexing given the large increase in incomes from meat and fish sales reported in the incomes survey and the program’s reported creation of 52 producer groups. These figures raise questions as to whether the increases in meat and fish sales were due to LEAP-sponsored producer groups or some other factor. Membership in rice seed bank groups and irrigation groups, two groups we did not ask about in our networks survey, appear to be substantially greater in LEAP communities than in control communities, although the former only showed significant increases for poor respondents and the latter only for non-poor respondents. Interestingly funeral group membership is no different between LEAP and control communities even though this was the one and only type of social group in our networks survey that exhibited significantly positive results. There was no difference between program and control communities in respondent’s participation in women’s groups—a bit of a disappointment given the focus of the SHG model on women. There were significantly more youth group members in program communities, although these extra members clearly came from the non-poor who were not targeted by the LEAP program. The average effect of the program on group membership shown in column 8 is a moderate 36 percent of a standard deviation and highly significant. This significant overall effect is due almost entirely to the greater participation in SHGs and rice seed banks in LEAP communities.

26
**Table 4: FDI Spillovers, by Investment Typology**

|||**High-gro**|**wth firms**|||**All f**|**irms**||
|---|---|---|---|---|---|---|---|---|
|VARIABLES|ALL|ES|MS|RS|ALL|ES|MS|RS|
|Linkages Channel|0.592**|2.950**|0.583*|-1.317|-0.051|0.228|-0.046|0.242|
||(0.256)|(1.447)|(0.347)|(2.065)|(0.051)|(0.175)|(0.064)|(0.401)|
|Demonstration Channel|0.161*|-0.033|0.216|0.322|0.004|-0.108**|0.010|-0.074|
||(0.084)|(0.281)|(0.142)|(0.227)|(0.019)|(0.042)|(0.032)|(0.078)|
|Log Age|-0.121***|-0.084|-0.191***|-0.068**|-0.056***|-0.070***|-0.068***|-0.027***|
||(0.023)|(0.070)|(0.049)|(0.033)|(0.005)|(0.017)|(0.009)|(0.009)|
|Exporter|-0.060|-0.190|-0.181**|0.041|-0.000|-0.011|0.016|-0.041**|
||(0.042)|(0.122)|(0.090)|(0.074)|(0.011)|(0.024)|(0.024)|(0.017)|
|Log Labor Productivity|0.101***|0.086*|0.118***|0.022|0.082***|0.059***|0.099***|0.056***|
||(0.013)|(0.049)|(0.022)|(0.018)|(0.005)|(0.010)|(0.008)|(0.012)|
|Constant|0.459|0.040|0.106|-0.456**|-0.816***|-0.212**|-0.979***|-0.278**|
||(0.286)|(0.542)|(0.384)|(0.198)|(0.060)|(0.107)|(0.098)|(0.110)|
|Observations|1782|172|642|341|31523|3150|11414|5569|
|R-Squared|0.291|0.351|0.348|0.256|0.166|0.118|0.163|0.130|

Note: This table shows the estimation of FDI spillovers by motivation, separately for high-growth firms and all domestic firms. ‘All’ indicates that the regression includes all types of investment. ‘ES’ includes only efficiencyseeking investment. ‘MS’ includes only market-seeking investment. ‘RS’ includes only natural resource-seeking investment. Standard errors (in parentheses) are clustered at the country-sector level. *** p<0.01, ** p<0.05, * p<0.1 Source: Author computation using data from the World Bank Enterprise Surveys.

# **4. Robustness Checks**

In this section, I analyze the robustness of my key result: that, on average across the developing world, high-growth firms are the main recipients of positive FDI spillover effects and that linkages are the more powerful transmission channel. I employ specification [7] in Table 3 to examine the robustness of the results to changes in the indicator of firm performance, measures of sales growth, and cut-offs to identify high-growth firms.

I first test the robustness of the results to an alternative indicator of firm performance. In addition to sales, the ESD provides information on employment growth during the last two years prior to when the survey was administered in each country. The results are reported in column 3 in Table 5. The finding that high-growth firms capture FDI spillovers from the linkages holds in this specification–the coefficient for the interaction term of the high-growth firms dummy and the linkages channel is positive and significant at the 1 percent level. The demonstration channel is not significant for any type of firm. While the coefficient of the impact of sectoral linkages for non-

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- 16 -

the most common form of tenure, and rental values are well known and easily accessible to the taxing authority, ARV may be tLe most appropriate way to define value. Where owner occupancy is the more common tenure form--and particularly where an active real estate market exists- -capital value may be more appropriate.

# CalculYatingValme

3.30 In reforming property taxation, the main issue to be addressed in valuation is not how value should be denominated but how it should actually be derived. Here again, procedural choices can make the difference between a system that delivers fair, defensible valuations at reasonable cost, and one that does not.

3.31 The purpose of tax valuation is to provide a basis for distributing the burden of the property tax. In considering standards and options for valuation, it is important to distinguish tax valuation from the valuation governments undertake when they intend to purchase a property outright. In the latter case, a high standard of accuracy is required: the valuation must produce an _absolute_ value in current market terms, as the amount changing hands will equal the entire value of the asset. Valuation for tax purposes, in contrast, requires only a determination of the _relative_ value of properties at a common point in time. As it involves an exchange equal only to a small percentage of the property's value, accuracy can be justifiably traded off in the interest of cost and administ:ative simplicity.

3.32 What is essential in a tax valuation system is objectivity--so as to reduce opportunities for dispute or collusion--- and a mechodology appropriate to local skills and the market information available in the local jurisdiction.

3.33 For Common Tvies of ProRertv. Use Mass Appraisal. There are fundamentally two approaches to valuation. The first relies on direct market information about the property being valued. The sesond depends on extrapolation, by formula, from a sample of properties; a practice termed mass appraisal.

3.34 The direct market information approach is chiefly ised in ARV countries in Africa and South Asia--the one-time colonies of France and Britain. Mass appraisal is used in both capital value countries---Brazil, Mexico, and the Philippines, among others--and to value owner-occupied properties in ARV countries. Some ARV jurisdictions--Anambra and Oyo states in iiigeria, for example--use mass appraisal systems to value both renter- and owner-occupied property.

3.35 Where it can be used, the direct market d-ta approach is potentially more accurate than mass appraisal. (As an indicator of market value, nothing beats the real thing.) But in practice the reverse is true. The direct market data approach fails the test of objectivity, and the absence of a formula-driven basis for valuation leaves the valuer vulnerable to bribery.

3.36 The Calcutta case is illustrative. There the valuer is instructed to value rental property on the basis of actual rents, and he is authorized to seek rent information--including rent receipts--from the occupants. Occupants,
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a long dme may elapse between execution of reforms and this recognition, leaving a balance of payments gap that needs to be filled for growth to occur.

(World Bank, 1992: 9) If such crowding in occurs then the initial aid may support increases in imports over and above the value of the aid itself.

(cl Aid apd debt service: some part of the aid may be intended to be used for debt relief. Accurate recording would show the inflow as aid receipts and the outflow as either net factor payments for interest relief or a reduced net capital inflow for amortization. If the relief is for principal payments on past aid then the net aid figure is unaffected by the debt relief if the debt would have not been paid in the absence of the relief. If the debt would have been paid then the debt relief is equivalen **t** o untied foreign exchange (and so may stimulate imports).

The above accounting points may apply if aid intended for imports is diverted to debt service. If repayment of principal is an important capital account item it is preferable to present the ,ata showing gross disbursements and amortization, rather than the net disbursement form used in the equations above.

(d) Changes in reserves: a part of an increased aid inflow may be added to reserves. Studies of the macroeconomic effects of counterpart fiuds - notably Roemer (1989) and Bruttn and Hill (1990 and 1991) - discuss this possibility. Such a response may be appropriate if there are likely to be Dutch disease effects from a temporary aid boom.

# _Internal and etaenrl balace_

Now consider how the internal (investment-savings) balance accommodates an aid inflow. First suppose aid to be a grant. Combining the definition: _GNS = GDS_ **_+_** _NFP_ **_+JMR_** (35) where GNS and GDS are gross national and domestic savings respectively, with die first identity in equation (3.1) gives: _GDS +_ **_NTR +_** _NFP - I_ **_=_** _X MR_ **_._** _NFP -_ **_(3,6)_** 34
detailed questions to identify migrants in the data are used extensively to analyze linkages between migration and the applicable issues.

The real challenge in survey design and data collection emerges in origin countries, especially among those that lack adequate statistical capacity. The absence of migrants from the household where data are collected only complicates matters further. Such survey data collection operations require reliance on proxy respondents, in most cases a family member, to answer the questions on behalf of the absent migrants. Various concerns arise from eliciting information through proxy respondents, including whether respondents remember or even know the answers. The information collected through proxies in the household or community of origin can be complemented and cross-checked with short interviews of the migrant themselves via other means, such as phone or online interviews. Alternatively, for certain types of migration, say seasonal or circular migration, proper timing of fieldwork may enable eliciting information at the point of origin directly from the migrant. Finally, interviews at the origin can be administered directly to returnee migrants, often using long recall periods.

Deciding how to identify migrants is the first step in ensuring that desired individuals are captured in an origin-country survey. In order to assess the impact of overall migration patterns, one should try to identify (1) all current household members with past experience with international migration over a given period – return migrants, (2) all former household members who are now living abroad – current migrants, and (3) all former household members with past international migration experience who now live in the source country but in a different household – non-member returnees. As mentioned, collecting information for each group presents different challenges, especially 15
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DOI:10.1080/07900627.2018.1515065 Timilsina, Govinda R. and Mike Toman (2016). Potential Gains from Expanding Regional Electricity Trade in South Asia. Energy Economics, Vol. 60, pp. 6-14, 2016

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World Bank. (2013). Integration of Electricity Networks in the Arab World: Regional Market Structure and Design. Report No: ACS7124. Midle East and North Africa (MENA) Regional Department, World Bank, Washington, DC.

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35
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49
|**Table 3: Maximum Likelihood NTX-Withdrawal Duration Models**||
|---|---|
|Weibull Distribution,|coefficient|
|(242 observations)|(z-score)|
|**Household characteristics**||
|Land assets||
|Land ownership, in cuerdas (_land_owned_)|0.002|
||(0.14)|
|Land ownership, squared|<br>-0.000|
||(-0.00)|
|Quality of best plot (_land_qual_)|0.068|
||(2.92)|
|Human capital assets||
|Age of household head (_age_)|-0.002|
||(-0.05)|
|Education of the head of household (_education_)|0.043|
||(1.18)|
|Education of the head of household, squared|<br>-.006|
||(-1.21)|
|Number of household adults (_adults_)|0.005|
||(0.26)|
|Other assets||
|Agricultural assets: index (_ag_assets_)|0.088|
||(3.21)|
|Durable goods: index (_durables_)|-0.071|
||(-3.21)|
|**Market conditions**||
|Average prices (_Price_ave_)|0.052|
||(2.12)|
|**Role of time in withdrawal**||
|Historical time: origin of withdrawal spell/time of adoption (_start_w_)|-0.058|
||(-5.85)|
|Historical time: adoption epoch dummy: 1990-2001 (_epoch_90-01_)|-0.025|
||(-0.19)|
|Historical time: adoption epoch dummy: 2002-2005 (_epoch_02-05_)|0.133<br>(0.70)|
|Village time: % adopters in the village (_Village_t_)|<br>-0.019|
||(-3.79)|
|**Community fixed effects**||
|<br>San Mateo|-0.122|
||(-1.09)|
|El Rejon|<br>1.099|
||(4.54)|
|Sta. Maria de Cauque|<br>0.0578|
||(0.60)|
|Pacul|<br>0.378|
||(2.61)|
|Pachali|<br>0.047|

28
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# **TABLE 14:** PETROCMDI[CALS - **NOMIRAL** PROTECTION RATES

|Product|Protective<br>Tariff|Import<br>Resime|Realized<br>Protection<br>(NPR.Z)a|Compensatory<br>ProtectionCl)|
|---|---|---|---|---|
|Intermediates|||||
|p-xylene|115|Canalized|110|42|
|MEG|148|OGL|64|36|
|PTA|208|Restricted|75|31|
|DMT|210|Restricted|75|24|
|ACN|110|Restricted|70|28|
|Caprolactam|72|Canalized|68|16|
|ABS/b|145|Canalized|77|55|
|Alpha-OlefinsXb|<br>95|OGL|77|82|
|MALb|115|OGL|81|47|
|PA/b|115|Canalized|110|32|
|Polyolefins|||||
|LDPE/LLDPE|57|OGL|14|43|
|HDPE|65|OGL|10|48|
|PP|50|OGL|20|32|
|PS|50|OGL|28|31|
|PVC|40|OGL|11|15|
|Synthetic Rubber|||||
|PBR|100|OGL|66|19|
|Buta Rubber /b|85|Canalized|77|68|
|EPM Rubber /b|85|Canalized|67|44|
|Synthetic Fibers|||||
|ASF|180|n.a.|137|24|
|PSF|213|Restricted|192|32|

La These price ratios, valid for one point of time (generally in 1988), are only indicative, given the volatility of domestic and international prices in recent years.

# /b Projected parameters for DFI subprojects.

56. The domestic prices given by realized protection are generally lower than the landed prices (CIF plus protective tariffs) and in turn higher than the protection required to compensate for the extra costs of capital and inputs (compensatory protection). Tariffs contain substantial amounts of Nwaterw introduced largely for the purpose of generating public revenue from
official and foreign minister, as Haiti's Prime Minister. Having determined that the situation in Haiti continued to constitute a threat to international peace and security in the region the Security Council decided to establish the United Nations Stabilization Mission in Haiti (MINUSTAH) and requested that authority be transferred from the Multinational Interim Force, authorized by the Security Council in February 2004, to MINUSTAH on June 1, 2004.

# **2.  Data and Methodology**

This section presents data sources and the methodologies used in the paper to analyze poverty and labor markets in Haiti.

## **Data**

Haiti is completing the first comprehensive household survey that covers both rural and urban areas. National household data are critical for making informed decisions on alleviating urban and rural poverty in Haiti. The analyses in this paper are based on the national households survey ( _l’Enqueête sur les Conditions de Vie Haïti_ — the Haiti Living Conditions Survey (HLCS)) from 2001 (still unreleased). Population data are from publications produced by the statistical office ( _Institut Haitien de Statistique et d’Informatique—_ IHSI). The survey was undertaken in all nine regions ( _department)_ and is representative at the regional level in Haiti. The dataset includes 7,186 households. It is the first time in Haiti’s history that a survey of this magnitude has been conducted. (See FAFO for more information.<sup>2</sup> ) The household survey consists of 15 SPSS files (these files are dated 10.06.2004 and named Base de Données Mar). The Bank obtained them directly from the Haitian statistical agency via FAFO the Norwegian institution that has worked with the statistical office. We have discovered a number of serious flaws. The most important flaw relates to the variable describing the metropolitan-urban-rural status of a household/individual, which is different in the different files. After discussions with the IHSI the only reliable data for metropolitan, urban, and rural levels are those based on the file with household information, therefore these data are used throughout the paper.

To calculate poverty, income including self-consumption has been used. Income is for the past 12 months based on a number of individual income sources and selfconsumption is estimated value of consumption (and barter) of household production of crops, meat, and fish during the last week. First respondents answer questions on consumption of own production, and the market value of it. Secondly an average unit price of each type of good was calculated for the whole sample and multiplied by the quantity consumed last week and multiplied by 52 weeks.

> 2 FAFO’s website: www.fafo.no.

3