人力资本、市场分割与农民工的工资决定

对农民工工资的最小二乘估计表明,在控制了其他变量以后,教育每增加1年,农民工的工资将提高6.1%,参加培训者比不参加培训者的工资要高出15.7%;行业垄断不仅造就了少数人的富裕也造成了多数人的贫困;市场化使人力资本和市场分割的工资效应均明显增强,这意味着消除劳动力市场分割和加强教育培训将是同等重要的政策手段。此外,在处理教育的内生性问题时发现,父母的受教育年限、兄弟姐妹数、调查地域的类型都不是理想的工具变量。     

A COMPARISON OF TOBIT AND OLS ESTIMATES OF JAPANESE PEANUT IMPORT DEMAND

A Tobit analysis is applied to estimate Japanese peanut imports under quota restrictions for the period 1973–1988, and to assess the bias when the presence of quota is ignored by using OLS estimation. The results show that biased estimates are obtained by using OLS in the presence of quota restrictions.     

Estimates of Mincerian Returns to Schooling in Nigeria

In the face of declining rates of primary and secondary school enrolment and increasing post-secondary school enrolment rates, the Nigerian government introduced the free universal basic education programme in 1999. To understand better the economic forces underlying the recent trends in school enrolment rates and appraise the new education policy from the perspective of private efficiency returns, I estimate the private returns to schooling associated with levels of educational attainment for wage and self-employed workers using data from the General Household Survey. The estimates for both men and women are small at primary and secondary levels, 2–3% and 4%, respectively, but are substantial at post-secondary education level, 10–15%. Inter-generational returns to schooling decline for primary education but rise for post-secondary education. These schooling return estimates may account for the recent trends in school enrolments. Thus, increasing public investment to encourage increased attendance in basic education is not justifiable on grounds of private efficiency, unless investments to increase school quality have higher private returns. With high private returns to post-secondary schooling, students at this level should pay tuition to recoup more of the public costs of schooling, which may be redistributed to poor families through scholarships.     

A revised Tobit procedure for mitigating bias in the presence of non-zero censoring with an application to milk-market participation in the Ethiopian highlands

Fixed transactions costs that prohibit exchange engender bias in supply analysis due to censoring of the sample observations. The associated bias in conventional regression procedures applied to censored data and the construction of robust methods for mitigating bias have been preoccupations of applied economists since Tobin [Econometrica 26 (1958) 24]. This literature assumes that the true point of censoring in the data is zero and, when this is not the case, imparts a bias to parameter estimates of the censored regression model. We conjecture that this bias can be significant; affirm this from experiments; and suggest techniques for mitigating this bias using Bayesian procedures. The bias-mitigating procedures are based on modifications of the key step that facilitates Bayesian estimation of the censored regression model; are easy to implement; work well in both small and large samples; and lead to significantly improved inference in the censored regression model. These findings are important in light of the widespread use of the zero-censored Tobit regression and we investigate their consequences using data on milk-market participation in the Ethiopian highlands.     

The Joint Estimation of Child Participation in Schooling and Employment: Comparative Evidence from Three Continents

This paper uses data from Peru, Pakistan and Ghana to analyse simultaneously child labour and child schooling, and compares them between these countries. We use a multinomial logit estimation procedure that analyses the participation and non-participation of children in schooling and in employment and, in particular, allows the possibility that a child combines schooling with employment or does neither. We also use an ordered probit estimation procedure based on a ranking of the various child schooling/employment/non-schooling/non-employment outcomes. The results point to both similarities and striking dissimilarities in the nature of child labour and child schooling between the chosen countries. For example, in Pakistan, but not in Peru, the girl child's ordering of schooling/employment outcomes shows her at a position of extreme disadvantage. Household poverty discourages a child from achieving superior outcomes, but the effect varies markedly across the three countries.     

Explaining changes in Sri Lanka’s wage distribution, 1992-2014: a quantile regression analysis

Sri Lanka experienced robust economic growth during the period 1992–2014 and had a decline in inequality due to wages rising fastest among low earners. The decline in inequality came almost entirely from rising rewards to low-skill labor, consistent with Sri Lanka’s comparative advantage in the global economy. However, educational and occupational upgrading served to widen wage gaps between the highest earners and the rest of the workforce. Using quantile regression analysis, this study also finds that selection bias overestimates average wages and underestimates the level of inequality, while exaggerating the extent to which women’s wages grew. It concludes with a discussion of the negative implications of persistent inequities across education, occupation, and gender, and recommends policies to address them.     

The Use of Maximum Entropy to Estimate Input-Output Coefficients From Regional Farm Accounting Data

This paper proposes the use of the Generalised Maximum Entropy (GME) method to estimate input-output coefficients, which reflect the unobserved allocation of farm input accounting costs to the various outputs produced. The GME method uses Shannon's information criterion as a basis for estimation. The performance of the GME method is compared with three other estimation techniques: Ordinary Least Squares (OLS), Bayesian estimation, and Linear Programming (LP). The various methods are applied to accounting data from a sample of beef-dairy farms in Brittany, France. The analysis shows that the GME method offers an interesting alternative to “traditional” estimation methods. In contrast with the latter, though, the GME method is suitable to handle easily the problems of singularity, constrained estimation, and zero-observations. Moreover, due to its flexibility, transparency and relative ease of implementation, the GME method is of great value to practitioners. However, the sensitivity of the GME estimates with respect to the design of the prior information set needs to be investigated further.     

Mismeasurement and efficiency estimates: Evidence from smallholder survey data in Africa

Smallholder agriculture in sub-Saharan Africa is commonly characterised by high levels of technical inefficiency. However, much of this characterisation relies on self-reported input and production data, which are prone to systematic measurement error. We show theoretically that non-classical measurement error introduces multiple identification challenges and sources of bias in estimating smallholders' technical inefficiency. We then empirically examine the implications of measurement error for the estimation of technical inefficiency using smallholder farm survey data from Ethiopia, Malawi, Nigeria and Tanzania. We find that measurement error in agricultural input and production data leads to a substantial upward bias in technical inefficiency estimates (by up to 85% for some farmers). Our results suggest that existing estimates of technical efficiency in sub-Saharan Africa may be severe underestimates of smallholders' actual efficiency and what is commonly attributed to farmer inefficiency may be an artefact of mismeasurement in agricultural data. Our results raise questions about the received wisdom on African smallholders' production efficiency and prior estimates of the productivity of agricultural inputs. Improving the measurement of agricultural data can improve our understanding of smallholders' production efficiencies and improve the targeting of productivity-enhancing technologies.     

Dynamics of rice prices and agricultural wages in the Philippines

Rice trade liberalization in the Philippines should decrease domestic rice prices impacting both agricultural wages and the welfare of agricultural wage earners. This study examines the short-run and long-run relationship between rice prices and agricultural wages in the Philippines using a neoclassical wage determination model. Three empirical frameworks are used—a cointegration/error correction framework, which assumes nonstationary variables in long-run equilibrium, a first difference model that assumes nonstationary variables but no long-run equilibrium, and an OLS framework that assumes the model variables are stationary. Conclusions are reasonably robust across the three empirical frameworks with wages adjusting positively to rice price changes with a short-run elasticity of 0.29 to 0.57, and a long-run elasticity of 0.70 to 1.0 in preferred models. An analysis of welfare implications suggests that although households that are heavily reliant on agricultural wages for income will be adversely affected by rice price decreases, other households will benefit.     

Where Does Education Pay Off in Sub-Saharan Africa? Evidence from Two Cities of the Republic of Congo

Using first-hand data from the 2009 Employment and Informal Sector Survey (EESIC) in the two largest cities of the Republic of Congo, Brazzaville and Pointe-Noire, we analyze the impact of education on labour market outcomes, and identify the segments where education pays off the most. Multivariate analyses of the risk of unemployment and sectoral choice indicate that young people face serious difficulties in the labour market: for most of them, their only choice is to remain unemployed or to join the informal sector. To measure the specific impact of schooling on earnings, we address issues related to sample selection and endogeneity of education in the earnings function. The results shed light on heterogeneity in the returns to schooling across the two main cities and institutional sectors. An important finding is that the informal sector does not systematically lag behind the formal sectors in terms of returns to education. We emphasize convex returns to education, meaning that the last years in secondary and tertiary schooling yield the highest returns, while those of primary education are generally lower. This convexity is also apparent in the informal sector, where education (albeit on another scale) again appears as an important determinant of earnings.     

Access to credit and heterogeneous effects on agricultural technology adoption: Evidence from large rural surveys in Ethiopia

Modern agricultural technologies hold huge potential for increasing productivity and reducing poverty in developing countries. However, adoption levels of these technologies have remained disappointingly low in Africa. This paper analyzes the effect of access to credit on the likelihood of adoption and use intensity of chemical fertilizers using data from large rural surveys in Ethiopia. Using a heteroscedasticity-based identification strategy to address the endogenous nature of access to credit, we find that access to credit has significant positive effects on adoption and intensity of use of chemical fertilizers. However, important heterogeneities are observed. Credit obtained from formal sources is more important for the intensity of use than for the decision to adopt chemical fertilizers. Credit taken with the primary purpose of financing agricultural inputs is more likely to promote adoption of chemical fertilizers than credit taken per se. Furthermore, reported credit effects are larger when estimated against the sample of credit-constrained non-users as compared with the pool of the whole sample of credit non-users. The results remain robust to several sensitivity analyses. Our results yield useful implications for the design, promotion, and targeting of credit services to leverage their effect on adoption of agricultural technologies.     

Boys' versus Girls' Schooling in Nepal: Does It Vary by the Extent of Mothers' Autonomy?

This paper hypothesises that resource allocation affecting the decisions relating to sons' versus daughters' schooling in Nepalese households is dependent on the extent of the mother's autonomy. Here, we posit that women's autonomy is a relative concept as a woman has degrees of decision-making power within her household. The results indicate that daughters' education is more likely to benefit when mothers solely make the decisions, but when decisions are made jointly with her spouse then the decisions are more likely to be in favour of sons' education. Our results indicate a marked gender difference in parental decisions over children's education, in the direction posited above, and less than 10% of mothers in the sample have complete autonomy over such decision-making. These results are important for policy-makers wishing to decrease gender bias in children's educational outcomes.     

Capturing household-level spatial influence in agricultural management using random effects regression

Data on agricultural and natural resource management typically have spatial patterns related to the landscapes from which they came. Consequently, econometric models designed to explain the determinants of humans' natural resource management practices or their outcomes often have spatial structure that can bring bias or inefficiency to parameter estimates. Although econometric tools are available to correct for spatial structure, such tools are largely lacking for use with discrete dependent variable models. While one obvious solution would be to develop the necessary tools, an alternative is to identify conditions under which spatial dependency can be managed effectively without formal spatial autoregressive models. This study examines conditions under which spatial structure corresponds closely to defined agro‐ecological zones, making it possible to model spatial effects by random effects regression. Using household survey data sampled along agro‐ecological zone strata, this article develops two models of links between farmer assets and agricultural natural resource degradation in southern Peru. The first stage model looks at determinants of crop yield loss over time (an index of soil productivity), while the second stage model looks at determinants of the extent of fallow cycles in crop rotation, a key agricultural practice reducing crop yield loss. Diagnostic statistics for spatial dependency reveal spatial structure, particularly in the fallow model. This spatial dependency is eliminated in the ordinary least squares (OLS) models by inclusion of the agro‐ecological zone random effects. In the spatially dependent fallow model, comparison of coefficient estimates between OLS and the spatial autoregressive maximum likelihood models showed OLS with random effects to give virtually identical results to the spatial autoregressive models, making the latter unnecessary. These results show that spatial structure in natural resource management models can sometimes be captured by zonal variables. When this occurs, random effects regression can largely eliminate spatial dependency. A necessary precondition for this approach with household survey data is prior sample stratification according to landscape characteristics. Where random effects models can effectively capture spatial structure, they may also offer analysts greater flexibility in analyzing models with limited dependent variables.     

Investigating the performance of different estimation techniques for crop yield data analysis in crop insurance applications

We investigate the performance of the ordinary least squares (OLS)‐, M‐, MM‐, and the Theil–Sen (TS)‐estimator for crop yield data analysis in crop insurance applications using Monte Carlo simulations. More specifically, the performance is assessed with respect to trend estimation, prediction of future yield levels, and the estimation of expected indemnity payments. In agreement with earlier findings, other estimators are found to be superior to OLS in simple regression problems if yield distributions are outlier contaminated and heteroscedastic. While this conclusion is also valid for subsequent applications such as yield prediction and the estimation of expected indemnity payments, the difference between the considered estimators becomes less distinct. For these applications, we find particularly the M‐estimator to be a good compromise between high‐breakdown (very robust) estimators and the very efficient OLS‐estimator. Because no regression technique dominates all others in all applications and scenarios for error term distributions, our results underline that the choice of the estimation technique should be dependent on the purpose of the crop yield data analysis. However, alternative estimators such as M‐, MM‐, and TS‐estimator can reduce (and bound) the risk of unreliable or inefficient crop yield data analysis in crop insurance applications.     

Determinants of Schooling in Egypt: The Role of Gender and Rural/Urban Residence

In this paper, we examine if there are gender differences in schooling attainment and the extent to which these differences are exacerbated for rural children in Egypt. Using a nationally representative cross-sectional survey, our estimation results find strong support for the hypothesis that being male and living in urban areas significantly improves child schooling. We show that relative to a female child who is “never enrolled” in school, a male child is over twice as likely to be currently attending school, and over two-and-a-half times more likely to have some schooling. These positive effects are particularly strong for rural male children. There are also regional variations, with a child (male or female) living in Upper Rural Egypt having a significantly lower likelihood of being currently enrolled. Finally, our estimation results point to large positive effects of father's education on the probability of current enrolment for all children. Mother's education, however, improves only the likelihood of current enrolment for female children, with no significant effect on male children.     

Smallholders,institutional services,and commercial transformation in Ethiopia

This article examines the role of institutional services of credit, input supply, and extension in the overall commercial transformation process of smallholder agriculture in Ethiopia. Survey data collected in 2006 from 309 sample households in three districts of Ethiopia are used for the analyses. Tobit regression models are used to measure the effect of access to services on the intensity of inputs use for fertilizer and agrochemicals. A probit model is used to measure these effects on the adoption of improved seeds. Intensity of use of seeds is analyzed using an ordinary least squares model. Logarithmic Cobb–Douglass functions are estimated to analyze the effect of access to services on crop productivity. Heckman's two‐stage estimation is used to examine determinants of household market participation and the extents of participation. Results show that access to institutional support services plays a significant role in enhancing smallholder productivity and market orientation. Our results imply that expanding and strengthening the institutional services is critical for the intensification and market orientation of smallholder agriculture in Ethiopia. In particular, appropriate incentives and regulatory systems are urgently needed to encourage the involvement of the private sector in the provision of agricultural services.     

Does maternal employment affect child nutrition status? New evidence from Egypt

Even though maternal employment can increase family income, several studies suggest that it could have adverse consequences on children’s health. In this study, we use a nationally representative sample of 12,888 children, aged 0–5 years from Egypt to examine the impact of maternal employment on child nutritional indicators, namely: stunting, wasting, and being underweight and overweight. We adopted various estimation methods to control for observable and unobservable household characteristics in order to identify the causal effect of maternal employment. These different techniques include, propensity score matching (PSM), OLS regression with controlling for a wide range of individual characteristics, and an instrumental variable two-stage least squares (IV 2SLS) approach. Results of the PSM and OLS suggest that maternal employment is weakly associated with having a malnourished child. On the other hand, the IV 2SLS suggests a stronger and significant association between maternal employment and poor nutritional status among children.     

Demand for a labor‐based drought insurance scheme in Ethiopia: a stated choice experiment approach

Index‐based weather insurance is increasingly used to manage weather‐related risks in smallholder agriculture. However, cash‐constrained smallholders often lack the resources to pay an insurance premium, which may undermine its wider adoption. This article investigates alternative insurance payment methods that may help to enhance the adoption of index‐based weather insurance. We use a choice experiment to elicit smallholders’ willingness to pay in cash or labor for index‐based weather insurance in four districts in the south‐central highlands of Ethiopia. The insurance schemes were created using a fractional factorial design with three factors: work, cash, and payout rate. We analyze the choice data using a random parameter mixed logit model. We find that the average participants need a subsidy to pay cash for insurance because their willingness to pay is less than the expected cost of the insurance. On average, they are willing to pay only 0.81 ETB (Ethiopian currency) to get an expected yearly payout of 1 ETB. However, most are willing to participate in work‐for‐insurance programs at lower daily wage rates than is common for other work programs in Ethiopia.     

In School or at Work? Evidence from a Crisis

This paper makes use of the income variability generated by the macroeconomic crisis of 2001/2002 to examine schooling outcomes in Argentina. The effect of this macroeconomic swing is examined with a focus on whether the income or substitution effect dominates in the decision-making of young people. It is demonstrated that the probability of being in school was 6.5–10 percentage points higher in May 2002 than in 2001 for 15–18-year-olds. This is probably the largest (positive) effect found in the developing country literature so far and is comparable to the effect of a 10% increase in household income. For 19–25-year-olds, the probability is between 2 and 6 percentage points higher. Results are robust to a wide range of controls and specification checks. Difference-in-difference panel estimation corroborates these findings and shows that the increase in schooling seems to be driven by a decrease in school exits during the crisis.     

Predicting versus testing: a conditional cross‐forecasting accuracy measure for hypothetical bias*

A measure of hypothetical bias, or the divergence between stated and revealed preferences, based on conditional cross‐forecasting accuracy is suggested, based on out‐of‐sample prediction accuracy when estimates from stated preference data are used in place of those from actual choices, and vice versa. We describe an application of this measure to assess hypothetical bias in the context of an inquiry into people’s willingness to pay to avoid canola oil produced from genetically modified plants. The analysis suggests the presence of groupwise hypothetical bias in these choice data.