rafmacalaba/datause-encoder-data huggingface dataset:
that the effect of a mean-preserving change in the standard deviation of the weather distribution leads to a reduction in r, portfolio riskiness, and therefore in farm profitability. The magnitude of the effect of an increase in weather riskiness, however, declines with the total wealth of the farmer if i) there is declining relative and absolute risk aversion or ii)<sup>i'</sup> < 0, wealth facilitates ex post consumption smoothing. Thus, wealthy or "large" farmers may possibly be more efficient than small farmers (and exhibit more variable incomes) in areas in which weather risk is sufficiently high, even if risk aversion does not depend on wealth, as long as the more wealthy are better able than the less wealthy to smooth consumption. Because the responsiveness of asset portfolios to risk depends on both preferences and on constraints, it is clear that the observed relationship between the moments of the profit distribution (profitability and riskiness in this case) by wealth class cannot alone be used to characterize preferences, as in Antle (1989). More importantly, the overall profitability of farmer asset portfolios and the inequality in the distribution of profits can be improved via interventions that do not necessarily require a redistribution of wealth; in particular those that reduce constraints on ex post consumption-smoothing; e.g., credit market improvements, weather insurance, or employment schemes may be as effective. However, as discussed in Binswanger and Rosenzweig (1976), covariance and moral hazard make the establishment of credit programs and insurance particularly difficult in rural areas, and the poor experience of such schemes is testimony to this difficulty (Hazell et a!., 1986). 2. The Data The preceding framework indicates that to test for the existence of an investment equilibrium conditioned by risk and to assess the interactions between total wealth holdings, agricultural risk and the composition of investment portfolios requires time-series data on investments, wealth and 8
“causal” links, we get an illusion of knowledge and discovery where there are none.

One practical implication of this observation is that it spells out the urgent need for a **Journal of Failed Experiments** or at least a publicly-available depository of such experiments so that we know how many people found a relation between M and P and how many did not. This will not solve all problems, since arguably, in each of the villages where researchers were looking for the relation between M and P, it is possible that M and P stood for different things from what others were looking for in other villages. If each underlying process entails the toss of a coin as in the above description, then we will not have evidence on the same test in many places, but different tests in different places. Nevertheless, it is important to keep track of failed experiments, in the sense of experiments that did not reveal any link between two variables. And such a journal, there can be little doubt, will have a sobering effect on economics, making evident where the presence of a result is likely to be a pure statistical artifact.

# 5. **Knowledge, Evolution and the Induction Principle**

Despite the skepticism of the previous sections, the fact remains that human beings know a lot. We “know” when we release a ball in mid-air, it will move down; we “know” what time the sun will rise tomorrow; we “know” that it is a virus that is the source of the common cold. Of course, all this can be the luck of the draw, implying that all this supposed knowledge worked thus far, but will not tomorrow. This cannot be ruled out formally, but intuition suggests there is more to these bits of knowledge than pure luck. At any rate, that is the presumption under which I will work. Human beings know a lot about nature or, more minimally, our minds are somehow synchronized with nature. We tend to observe patterns in nature, where indeed there are patterns. And most of what our mind knows it does simply by picking up knowledge along the way without pausing to think if the knowledge has scientific basis and if it will stand the test of randomization.

15
our second-stage regression: When compared with Equation (1), _A_<sup>_k_</sup> _t_<sup>isthevectorofdestinationspecificparameters</sup> from Equation (3). The gender-specific destination pull variables, _λ_<sup>ˆ</sup><sup>_k_</sup> _g,t_<sup>arethoseestimates</sup> obtained from our first-stage regression, Equation (2). Our two-step procedure up until this point, which aims to maximize the accuracy of our predictions, comes at a cost; our genderspecific destination pull variables, _λ_<sup>ˆ</sup><sup>_k_</sup> _g,t_<sup>_,_willbecorrelatedwiththevector</sup><sup>_Ak_</sup> _t_<sup>ofdestination</sup> specific variables. In turn, this means that it is impossible to meaningfully interpret _A_<sup>_k_</sup> _t_ and as such these results are not reported. Given that more data exist in 2000, when compared to 1990 and again, so as to maximize the accuracy of our predictions, for each gender-education pair we run regressions for both 1990 and 2000 simultaneously, allowing our explanatory variables to vary over time, but additionally forcing the coefficients on these variables to be constant in both years.

Until this point, we have four separate gender-education pairs: high-skilled men, highskilled women, low-skilled men and low-skilled women. In our final step, we take our predictions for the missing cells from Equation (4) and apply the resulting shares to the totals detailed in OPSW. Since these data provide the most accurate estimates of global migrant stocks, we are, in effect, splitting the OPSW data into the relevant education-gender bilateral migrant stocks. Herein lies the final econometric issue that needs addressing, namely 19
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9 owning no more than a few percent in a given enterprise. On the upper end, (concentrated ownership), there are venture capital or so-called turn-around funds which are often major owners in portfolio enterprises and often provide capital and management resources to restructure an enterprise. In the Czech and Slovak Republics, funds may own up to 20% in a given enterprise, and thus they lie in the middle of the above-mentioned extremes.

**Table 4: Supply (shares) and demand (voucher points) in the first wave of privatization**

|||Bidd<br>|ing Ro<br>|und<br>||||**%**<br>|
|---|---|---|---|---|---|---|---|---|
||1|2|3|4|5|TOTAL|available|matched|
|voucher points used (billion)|2.98|3.41|1.02|0.51|0.52|8.44|8.56|98.6|
|Number of shares sold (million)|89.4|77.8|32.5|37.1|40.9|277.7|299.4|92.8|
|average number of points per share|33.3|43.8|31.4|13.7|12.7|30.4|28.6|-|
|share transfer per 1,000 points|30.0|22.8|31.9|72.7|78.7|32.4|35.0||
|Source: Mejstrik et al. (1994).|||||||||

How did the funds select their portfolios? Two strategies are possible. First, a fund, like any other investor, could use its points for more expensive shares (more points per share) or cheaper shares (fewer points per share). Over the five bidding rounds, the difference between the most expensive and the cheapest share was 600:1". Second, a fund could invest in a dispersed portfolio with many enterprises or in a concentrated portfolio with only a few enterprises. Since every fund has a limited number of points, the two aspects are related.

In order to evaluate whether funds invested in cheaper or more expensive shares, one can compare the book value of shares acquired per voucher book invested. The book value of each share was set at CSKI,000, and one voucher book consisted of 1,000 investment points that each citizen over 18 years of age was eligible to purchase for CSKI,035 ($35 which amounts to 25% of an average monthly income at that time). The higher the average I IFor a more detailed analysis of the investment procedure over the five bidding rounds see Shafik (1993 and 1994).
De Paoli, B., and P. Zabczyk. 2013. “Cyclical Risk Aversion, Precautionary Saving, and Monetary Policy.” Journal of Money, Credit and Banking 45(1): 1–36.

Eggertsson, G. B., and P. Krugman. 2012. “Debt, Deleveraging, and the Liquidity Trap: A FisherMinsky-Koo Approach.” Quarterly Journal of Economics 127(3): 1469–1513.

Fatás, A. and I. Mihov. 2009. “Why Fiscal Stimulus is Likely to Work.” International Finance 12(1): 57-73.

Favero, C., and F. Giavazzi. 2007. “Debt and the Effects of Fiscal Policy.” NBER Working Paper 12822, National Bureau of Economic Research, Cambridge.

Favero, C. A., and F. Giavazzi. 2010. “Reconciling VAR-Based and Narrative Measures of the Tax-Multiplier.” CEPR Discussion Paper 7769, Centre for Economic Policy Research, London.

Favero, C., F. Giavazzi and J. Perego. 2011. “Country Heterogeneity and the International Evidence on the Effects of Fiscal Policy.” IMF Economic Review 59(4): 652-682.

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Galí, J., J. D. López-Salido, and J. Vallés. 2007. “Understanding the Effects of Government Spending on Consumption.” Journal of the European Economic Association 5(1): 227–270.

Giavazzi, F., and M. Pagano. 1990. “Can Severe Fiscal Contractions Be Expansionary? Tales of Two Small European Countries.” In NBER Macroeconomics Annual 1990, Volume 5, edited by O. J. Blanchard and S. Fischer, 75–111. Cambridge: MIT Press.

Giavazzi, F., and M. Pagano. 1996. “Non-Keynesian Effects of Fiscal Policy Changes: International Evidence and the Swedish Experience.” Swedish Economic Policy Review 3(1): 67– 103.

Gilchrist, S., and E. Zakrajšek. 2012. “Credit Spreads and Business Cycle Fluctuations.” American Economic Review 102(4): 1692–1720.

Guajardo, J., D. Leigh, and A. Pescatori. 2014. “Expansionary Austerity? International Evidence.” Journal of the European Economic Association 12(4): 949–968.

Gupta, S., J. T. Jalles, C. Mulas-Granados, and M. Schena. 2017. “Governments and Promised Fiscal Consolidations: Do They Mean What They Say?” IMF Working Paper 17/39, International Monetary Fund, Washington, DC.

Harding, D., and A. Pagan. 2002. “Dissecting the Cycle: A Methodological Investigation.” Journal of Monetary Economics 49(2): 365–381.

Ilzetzki, E., E. G. Mendoza, and C. A. Végh. 2013. “How Big (Small?) are Fiscal Multipliers?” Journal of Monetary Economics 60(2): 239–254.

Jordà, Ò. 2005. “Estimation and Inference of Impulse Responses by Local Projections.” American Economic Review 95(1): 161–182.

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16
grants is much larger than an equivalent increase in income. Economists tend to regard this finding as anomalous in that it contradicts the standard theoretical result from the unitary model of local government decision making. In this model the local authority is thought of as a single representative consumer, or median voter, who will treat the aid as ordinary income. In this case, the flypaper effect suggests irrationality. However, a number of theoretical papers have constructed models under which a flypaper effect can exist in reality.

The recipients of aid ─ provinces and communes in Vietnam ─ are heterogeneous entities. Then, it is no longer clear that there is anything “anomalous” about the flypaper effect. Indeed, Roemer and Silvestre (2002) show that when outcomes are determined by an electoral process, the general presumption will be some degree of flypaper effect. They show that the complete absence of a flypaper effect requires rather special conditions: namely that incomes are essentially shared the same way as the tax burden. The relevance of this kind of theoretical model to Vietnam, where local governmental processes are not electoral, is questionable. However, the general point of Roemer and Silvestre (2002) remains, namely that collective decision making processes with heterogeneous preferences within recipient governments can sometimes generate flypaper effects.

A large developed country literature has grown around investigating and explaining this common empirical finding (for an overview see Hines and Thaler, 1995). Similarly to the fungibility literature, the empirical work largely relies on cross-sectional or pooled cross-sectional time series data on grants to (in this case within country) localities such as states or school districts.

There have been few applications of this literature to developing countries. An exception, though in a quite different context, is Jacoby’s (2002) study of whether child consumption increases commensurately to food intake as a result of participation in a school feeding program in the Philippines. In common with Jacoby (2002), this paper uses a quasi-experimental design. This differs in a number of ways from the past work on fungibility and the flypaper effect in the context of grants to local governments.

The first major difference concerns the level of aggregation. There appears to be little evidence based on actual development projects, which are often implemented at the 4
**Table S3: Effects of Insurance Enrollment on Visits Among Parents**

||Any Provider|Pharmacy|EMP|Public Facilities|Private Facilities|
|---|---|---|---|---|---|
|Panel A: Ever Visit|(1)|(2)|(3)|(4)|(5)|
|Parent Enrolled|-0.053|-0.045|0.412***|-0.134*|-0.033|
||(0.048)|(0.061)|(0.037)|(0.072)|(0.072)|
|Constant|1.019***|1.173***|-0.064|1.071***|-0.419*|
||(0.156)|(0.198)|(0.120)|(0.239)|(0.223)|
|Observations|1614|1614|1614|1614|1614|
|R-squared|0.01|0.02|0.289|0.059|0.055|
|Panel B: Number of Visits|(1)|(2)|(3)|(4)|(5)|
|Parent Enrolled|0.968|0.748|1.388***|-0.624|-0.190|
||(1.000)|(0.563)|(0.203)|(0.411)|(0.292)|
|Constant|6.163*|3.332*|-0.545|5.141***|-1.085|
||(3.199)|(1.889)|(0.625)|(1.585)|(0.982)|
|Observations|1614|1614|1614|1614|1614|
|R-squared|0.046|0.017|0.141|0.053|0.038|

_Notes:_ The sample is all parents (N=1614). Above regressions are estimated coefficients from 2SLS-IV estimates where "Parent Enrolled" is instrumented with random assignment status. The dependent variable in Panel A is whether or not the parent has visited various providers over the past year. The dependent variable in Panel B is the number of times the parent has visited various providers over the past year. Regressions control for household size, household size squared, the inverse hyperbolic sine of parental income, parent's years of education, gender, whether the parent was sick in the past year, the number of times sick, total number of health visits, and survey round and market fixed effects. Individuals without valid income data were imputed to be the median and regressions were run with a dummy variable indicating the missing value. Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1 _Source:_ Authors’ analysis based on data described in paper.

3
# **_What would be the transport requirement in case of dramatic increased production?_**

In case of significant increase of agricultural productivity, with an average of 1 hectare per household, annual production would hardly reach 8-10 tonnes, which is at least 3 to 4 times the current production (see Table 10). However, in terms of transport demand, this is still not equivalent to a truckload per year. Therefore, even though a season would last only a couple of months, the transport equivalent would be limited to 300-400 kilogrammes per week, which means that infrastructure-wise, a paved, allweather road would not be necessarily needed and IMTs<sup>27</sup> , with appropriate infrastructure, could bridge the last mile gap.

# **Table 10: Actual and potential yield per household in selected districts in Uganda (in kgs)**

|**District**|**Crop**|**Actual **|**Potential **|**_Ratio potential/actual_**<br>**_production_**|
|---|---|---|---|---|
|Busheni|Bananas|960|6,719|_7.0_|
|y|Beans|200|683|_3.4 _|
|Tororo|Cassava|19,000|41,503|_2.2 _|

Note: actual data extracted from household surveys; potential data derived from FAO model.

It brings data to what Metschies (1998) had already pointed out: infrastructure and transport services requirements are correlated with agriculture type. For small shareholders based, who depend on subsistence agriculture, agricultural surplus is so low that it cannot lead to transportation by truck and therefore the infrastructure requirement should be limited to fulfill IMTs demand. In the case of larger plot sizes (and increased productivity) and even better mechanized agriculture, roads are needed for trucks.

> 27 Intermediate means of transport (IMT) can increase the carrying capacity and speed, reducing transport costs. If markets are too far to walk (one way 10 – 15 km) is often regarded as the threshold for access to markets. A pack animal can extend the distance to 20 km in hilly areas, a bicycle to 30 km in flat terrain and a single-axle tractor with trailer covers up to 50 km (Hine and Ellis, 2001). Thus, IMT make new markets accessible where producer prices might be higher; new products might be demanded, or inputs might be cheaper. For long distances the use of motor vehicles is essential.

31
# **Findings**

## **Women often underreported their economic activity**

The key finding is that most women in the visited communities reported engaging in market activities for pay or in production of goods for own-consumption that fit within the definition of employment. Yet most did not respond affirmatively to the questions posed by the household survey. That is, there is a clear disconnect between the definition of employment as meant to be captured in the labor force survey and the definition used by women (and men) in the rural communities visited for this research.

The interviews began with the two key questions included in the 2015 EPHPM used to measure employment.<sup>15</sup> Women who answered yes to the question of paid work typically reported paid employment outside of the home or working in a part-time paid activity from home such as grinding corn or washing clothes for others. At the same time, the qualitative study found that, overwhelmingly, women in both types of communities (those with and those without the presence of cooperatives) were likely to answer ‘no’ to the two questions that aim to capture economic activity - despite working in market activities. Significant discrepancies arose between women’s initial response to either one of the EPHPM survey questions measuring labor force participation and their later reports of actual tasks performed by them suggesting underreporting of work among women. Specifically, in response to the question "During the past week, did you dedicate an hour or more to any work or activity with payment in cash or in kind, or did you get any income? (except housework)", more than half of individually interviewed women responded ‘no’ even though they later described having realized activities for pay.

With regards to the second survey question applied to measure employment (During the past week, did you perform or help carry out any work, with relatives or individuals, without pay? (Except household work)”), a discrepancy could also be noted among those who initially responded no, but later reported engaging in economic activities without pay such as helping their partners perform agriculture related activities (watering, collecting and cleaning the production), performing volunteer work in their communities, or engaging in production activities related to sustaining the home (such as collection of firewood and livestock/poultry rearing for own consumption).

In contrast, men more consistently and unequivocally responded ‘yes’ to the household survey question on economic activity with payment in cash or in kind despite largely working in agricultural selfemployment. In fact, the only male interviewee to clearly respond ‘no’ was a 72-year old man, who stopped working because of age.

15 Q1: "During the past week, did you dedicate an hour or more to any work or activity with payment in cash or in kind, or did you get any income? (Except housework)"; Q 2: “During the past week, did you perform or help carry out any work, with relatives or individuals, without pay? (Except housework)”.

13
rules for information exchange, shape firm behavior and ensure quality in GVCs. They enable the codification of both product and process specifications to ensure that a wide range of global suppliers can consistently deliver end products that meet the quality requirements of developed-country markets. They are industry-specific and constantly evolving. Failure to comply with these standards can result in exclusion from the GVC.” (Gereffi, Fernandez-Stark and Psilos., 2011, p. 243) According to a recent business survey in the agri-food sector (OECD-WTO, 2013c – NB: 250 lead firms and suppliers in developing countries participated to the survey), about 60% of the firms pointed at the ability to meet quality and safety standards as the main factor influencing sourcing and investment decisions in GVCs. Similarly, 40% of the firms surveyed pointed at the non-compliance with mandatory import requirements as a typical trade problem in dealing with developing country suppliers. About 37% of the firms suggested that the improvement of standards infrastructure and certification capacity would be the most effective way to bring new developing country suppliers into GVCs, and almost half of the firms providing trade technical and capacity building efforts did focus on compliance with safety and quality standards.

Standards of relevance include both process (e.g., the respect of management, labor or environmental standards, often included in a CSR or conduct code) and product (e.g., quality) standards. These need to be respected throughout the value chain since every stage of production could affect the quality of the final product or service, and engage the responsibility and reputation of the lead firm in the country of final consumption of the product or service. In the agri-food business, this translates into “traceability” requirements aimed at protecting the health and increasing the information of consumers.

Standards in GVCs are both public and private, with an increasing prevalence of “voluntary” standards that are imposed by the lead firms (either buyers or producers) to all the input providers and assemblers along the chain (see Lee, Gereffi and Beauvais, 2012). Figure 16 provides an illustration of this public/private standards spectrum for the agri-food business. Despite this role of private standards in GVCs, public standards, public infrastructure for certification/accreditation, and the enforcement by public authorities of health/safety/environmental rules are essential to attract GVC production segments. Inadequate public standards can unduly raise the cost of local production and/or create unnecessary obstacles to trade.

**Figure 16. Standards in agri-food GVCs**

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