Parametric and nonparametric statistical modelling of crop yield: implications for pricing crop insurance contracts

This article considers alternative methods to calculate the fair premium rate of crop insurance contracts based on county yields. The premium rate was calculated using parametric and nonparametric approaches to estimate the conditional agricultural yield density. These methods were applied to a data set of county yield provided by the Statistical and Geography Brazilian Institute (IBGE), for the period of 1990 through 2002, for soybean, corn and wheat, in the State of Paraná. In this article, we propose methodological alternatives to pricing crop insurance contracts resulting in more accurate premium rates in a situation of limited data.     

Bivariate income distributions for assessing inequality and poverty under dependent samples

As indicators of social welfare, the incidence of inequality and poverty is of ongoing concern to policy makers and researchers alike. Of particular interest are the changes in inequality and poverty over time, which are typically assessed through the estimation of income distributions. From this, income inequality and poverty measures, along with their differences and standard errors, can be derived and compared. With panel data becoming more frequently used to make such comparisons, traditional methods which treat income distributions from different years independently and estimate them on a univariate basis, fail to capture the dependence inherent in a sample taken from a panel study. Consequently, parameter estimates are likely to be less efficient, and the standard errors for between-year differences in various inequality and poverty measures will be incorrect. This paper addresses the issue of sample dependence by suggesting a number of bivariate distributions, with Singh–Maddala or Dagum marginals, for a partially dependent sample of household income for two years. Specifically, the distributions considered are the bivariate Singh–Maddala distribution, proposed by Takahasi (1965), and bivariate distributions belonging to the copula class of multivariate distributions, which are an increasingly popular approach to modelling joint distributions. Each bivariate income distribution is estimated via full information maximum likelihood using data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey for 2001 and 2005. Parameter estimates for each bivariate income distribution are used to obtain values for mean income and modal income, the Gini inequality coefficient and the headcount ratio poverty measure, along with their differences, enabling the assessment of changes in such measures over time. In addition, the standard errors of each summary measure and their differences, which are of particular interest in this analysis, are calculated using the delta method.     

A worldwide analysis of trend in crop yields and yield variability: Evidence from FAO data

The trend in crop yields and yield variability affects food security and impact agricultural and food policies. Recent studies in this area have either focused only on one country or performed global analysis on a handful of crops. We provide the first worldwide analysis of trend and variability for 8088 country-crop yield series taken from the FAO database, employing a robust estimator to cope with the adverse statistical effects of outliers. More than half of the series display a slowdown in yield growth due to a closing of the gap between realised and attainable yields as well as to agricultural policies promoting more sustainable agricultural practices. Around one fourth of the series show also an increase in yield variability as a consequence of climate change and changes in farm management practices. Yield variability is highest in Eastern Europe, Central Asia and Middle East and North Africa, where food security may be threatened.     

Equilibrium Search with Continuous Productivity Dispersion: Theory and Nonparametric Estimation

In this article we develop an equilibrium search model with a continuous distribution of firm productivity types within a given labor market. We characterize equilibrium, derive expressions for the endogenous equilibrium wage distributions, and characterize the set of wage distributions that can be generated by the model. We develop a structural nonparametric estimation method for the productivity distribution. We estimate the model using French longitudinal survey data on labor supply, and we compare the results with those from a French panel data set of firms. The results are informative on the degree to which firms exploit search frictions.     

Nonparametric kernel estimation applied to forecasting: An evaluation based on the bootstrap

The results reported in this paper lend support to the nonparametric approach to estimating regression functions. This conclusion is based on a comparison of two sets of eight quarterly forecasts of U.S. hog supply generated by a well specified parametric dynamic model and by nonparametric kernel estimation. Despite the relatively small sample size, the nonparametric point forecasts are found to be as accurate as the parametric forecasts according to the mean square error and mean absolute error criteria. Bootstrap resampling is used to estimate the distributions of the forecast errors. The results of this exercise favour the nonparametric forecasts, which are found to have a tighter distribution.     

Using BS-PSD-LDA approach to measure operational risk of Chinese commercial banks

The research of operational risk management among Chinese commercial banks is still in its preliminary stage. Operational risk events are rare and data is hard to collect. This leads to very small data samples. Besides, a large number of empirical researches show that the distributions of operational losses are often skewed with fat tails. To address these issues, this paper puts forward a loss distribution approach (LDA) based on bootstrap sampling and piecewise-defined severity distribution (BS-PSD-LDA). The approach divides data samples into two distinct parts (high-frequency low-severity losses and low-frequency high-severity losses), and fits the two parts by lognormal distribution and Generalized Pareto distribution respectively. Using hand-collected samples of 426 operational losses in Chinese commercial banks during 1994–2010, we estimate the magnitude of operational losses using the BS-PSD-LDA method. We show that our method provides a better fit than the traditional parametric methods. Besides, the method using historical simulation of nonparametric method seems to offer a good fit to the sample as well. However, we believe that the BS-PSD-LDA approach offers improvement from the perspective of satisfying risk control requirement of the regulatory authority and ensuring the efficiency of funds' utilization.     

Weather Index Drought Insurance: An Ex Ante Evaluation for Millet Growers in Niger

In the Sudano-Sahelian region, which includes South Niger, the inter-annual variability of the rainy season is high and irrigation is limited. As a consequence, bad rainy seasons have a massive impact on crop yield and regularly result in food crises. Traditional insurance policies based on crop damage assessment are not available because of asymmetric information and high transaction costs compared to the value of production. We assess the risk mitigation capacity of an alternative form of insurance which has been implemented at a large scale in India since 2003: insurance based on a weather index. We compare the efficiency of various weather indices to increase the expected utility of a representative risk-averse farmer. We show the importance of using plot-level yield data rather than village averages, which bias results due to the presence of idiosyncratic shocks. We also illustrate the need for out-of-sample estimations in order to avoid overfitting. Even with the appropriate index and assuming substantial risk aversion, we find a limited gain of implementing insurance, which roughly corresponds to, or slightly exceeds, the cost observed in India for implementing such insurance policies. However, when we separately treat the plots with and without fertilisers separately, we see that the benefit of insurance is slightly higher in the former case. This suggests that insurance policies may slightly increase the use of risk-increasing inputs such as fertilisers and improved cultivars, and hence improve average yields, which remain very low in the region.     

The relation between municipal and government bond yields in an era of unconventional monetary policy

In this paper, we investigate how the 5‐year Swedish municipal bond yield has been related to the corresponding yield on government bonds during the period that the Riksbank has conducted unconventional monetary policy in terms of bond purchases. Using daily Swedish data on bond yields from February 2015 to January 2018, we first conduct an event study to assess the short‐run effects of the Riksbank's bond‐purchase announcements. We then estimate bivariate vector autoregressive models to study the dynamic relationship between the yields. Results from the event study suggest that the accumulated short‐run effect of the Riksbank's announcements was to lower the government bond yield by approximately 40 to 50 basis points and municipal bond yields by 30 to 35 basis points. Our vector autoregressive analysis indicates—in line with the event study—that an unexpected decrease in the government bond yield initially increases the municipal bond‐yield spread. However, after approximately 4 weeks, the effect has been reversed and the municipal bond‐yield spread is lower than it was initially. By conducting this analysis, we contribute to the understanding of the transmission of unconventional monetary policy.     

参与式灌溉管理对农业生产和收入的影响-基于淮河流域的实证研究

参与式灌溉管理可以实现政府和农户的双赢。基于淮河流域的农户调查数据,分析了参与式灌溉管理对农业生产和收入的影响。结果表明,参与式灌溉管理可以提高灌溉系统的维护水平、改善用水分配,进而能提高灌溉需水量大的作物的单产,而且在具体作物之间,这种显著的增产效果存在差异。参与式灌溉管理能提高农户种植业收入,低收入农户从中获益更多。     

Vasicek模型下寿险责任准备金评估

在假定寿险产品定价利率固定,准备金评估利率基于长期国债收益率且符合Vasicek模型等前提下,该模型适合我国目前的长期国债收益率。然后推导出随机利率下全离散型寿险责任准备金评估公式,并以Vasicek模型为例,使用蒙特卡罗模拟方法计算出准备金分布,同时对准备金在利率波动条件下的充足性做出分析。     

Efficiency in banking: a meta-regression analysis

One learns two main lessons from studying the great quantity of banking efficiency literature. These lessons regard the heterogeneity in results and the absence of a comprehensive review aimed at understanding the reasons for this variability. Surprisingly, although this issue is well-known, it has not been systematically analyzed before. In order to fill this gap, we perform a Meta-Regression-Analysis (MRA) by examining 1661 efficiency scores retrieved from 120 papers published over the period 2000–2014. The meta-regression is estimated by using the Random Effects Multilevel Model (REML) because it controls for within- and between-study heterogeneity. The analysis yields four main results. First, parametric methods yield lower levels of banking efficiency than nonparametric studies. This holds true even after controlling for the approach used in selecting the inputs and outputs of the frontier. Secondly, we show that banking efficiency is highest when using the value-added approach, followed by estimates from studies based on the intermediation method, whereas those based on the hybrid approach are the lowest. Thirdly, efficiency scores are also determined by the quality of studies and the number of observations and variables used in the primary papers. As far as the effects of sample size, dimension and quality of papers are concerned, there are significant differences in sign and magnitude between parametric and nonparametric studies. Finally, cost efficiency is found to be higher than profit efficiency. Interestingly, MRA results are robust to the potential outliers in efficiency and sample size distributions.     

Scope economies and technical efficiency of cocoa agroforesty systems in Ghana

A number of studies have addressed issues relating to the physiological, environmental and economic values of trees in cocoa farming systems. However, to date, little has been done to quantitatively examine the effect of crop diversity on cocoa farming efficiency. This study therefore sets out to first investigate whether and to what extent crop diversity (defined as the mixing of cocoa with other crop species on farmers' plots) affects productivity on cocoa farms. Secondly, it sought to establish whether there are economies of scope (i.e., cost complementarities) from the sharing of farm inputs by crops on the same plots. Our results indicate that diversified (i.e., multi-crop) cocoa farms are more efficient than single (i.e., mono) crop farms. Furthermore, our estimate for the economies of scope parameter indicates possibilities for cost complementarities between production of cocoa and other crops on the same plot. We advocate further investigation on the issue of scope economies to determine which crop combinations offer better cost complementarities and also meet biodiversity conservation objectives.     

Tail dependence analysis of stock markets using extreme value theory

Financial risk modelling frequently uses the assumption of a normal distribution when considering the return series which is inefficient if the data is not normally distributed or if it exhibits extreme tails. Estimation of tail dependence between financial assets plays a vital role in various aspects of financial risk modelling including portfolio theory and hedging amongst applications. Extreme Value Theory (EVT) provides well established methods for considering univariate and multivariate tail distributions which are useful for forecasting financial risk or modelling the tail dependence of risky assets. The empirical analysis in this article uses nonparametric measures based on bivariate EVT to investigate asymptotic dependence and estimate the degree of tail dependence of the ASX-All Ordinaries daily returns with four other international markets, viz., the S&P-500, Nikkei-225, DAX-30 and Heng-Seng for both extreme right and left tails of the return distribution. It is investigated whether the asymptotic dependence between these markets is related to the heteroscedasticity present in the logarithmic return series using GARCH filters. The empirical evidence shows that the asymptotic extreme tail dependence between stock markets does not necessarily exist and rather can be associated with the heteroscedasticity present in the financial time series of the various stock markets.     

Climatic impacts across agricultural crop yield distributions: An application of quantile regression on rice crops in Andhra Pradesh,India

Climatic impact on agricultural production is a serious concern, as it is directly linked to food security and poverty. Whereas there are empirical studies that examine this issue with parametric approaches focusing on the “mean” level of variables, few studies have addressed climatic impacts in general settings. Given this paucity, we characterize the impacts on crop yield distributions with a non-parametric approach. We examine the case of rice yield in Andhra Pradesh, India, an important state producing rice as a main crop but reported to be vulnerable to climate change. Employing 34 years of data, we apply quantile regressions to untangle the climatic impacts across the quantiles of rice yield, finding three main results. First, substantial heterogeneity in the impacts of climatic variables can be found across the yield distribution. Second, the direction of the climatic impacts on rice yield highly depends on agro-climatic zones. Third, seasonal climatic impacts on rice yield are significant. More specifically, a monsoon-dependent crop is more sensitive to temperature and precipitation, whereas a winter crop remains largely resilient to changes in the levels of climate variables. These findings clarify the idiosyncratic climatic impacts on agriculture in India, and call for location- and season-specific adaptation policies.     

The real rate of protection: the income and insurance effects of agricultural policy

Agricultural price policies in developed countries aim at protecting farmers against both low and volatile world market prices. However, traditional indicators of protection only refer to the income (level) effect of policy. Following other research, it is argued that public policy can also yield an insurance (stabilizing) effect. In this paper a way to measure these dual effects is proposed. The method is illustrated with wheat market data for the USA and the European Union. Strong evidence is found that the insurance effect is an important component of protection, albeit a small one relative to the income effect. Policy support provided higher income and lower insurance effects in the EU than in the USA. For both markets, policy reforms in the 1990s led to significantly reduced income effects and smaller insurance effects. Without accounting for the influence of policy on income variability, traditional measures of protection will understate the real rate of protection.     

区域性生态农业建设的作物配置新策略的研究

本文针对现行作物分类法的局限性，运用农业生态经济系统的功能性原理，提出一种新的作物分类法，以作物生产过程所表现的主体功能为依据将作物分成三大类型即社会型、经济型和生态型，并对每一类型作物的基本特性和增产增效对策进行了系统分析。在此基础上，提出了区域性生态农业建设中农田作物的合理配置的新策略。     

Small and Productive: Kenyan Women and Crop Choice

The question of gender differences in agricultural productivity has received particular attention in the development literature. The stylized fact that women produce less than men, while on average occupying smaller farms, presents a quandary as it is also a stylized fact that smaller farms have higher yields per unit of area. Using data from the 2006 Kenya Integrated Household Budget Survey, this study examines whether there is a gap in output per acre between men and women farmers in Kenya. Using ordinary and two-stage least-squares (OLS and 2SLS) analyses, it shows that when crop choice is taken into account, women are as productive as men. Specifically, the study finds that market-oriented crops are the source of differences. This suggests that further research into what determines crop choice is needed, in addition to policy that ensures that women have the same access as men to support for market-oriented crops.     

Underreporting of Top Incomes and Inequality: A Comparison of Correction Methods using Simulations and Linked Survey and Tax Data

Household surveys do not capture incomes at the top of the distribution well. This yields biased inequality measures. We compare the performance of the reweighting and replacing methods to address top incomes underreporting in surveys using information from tax records. The biggest challenge is that the true threshold above which underreporting occurs is unknown. Relying on simulation, we construct a hypothetical true distribution and a “distorted” distribution that mimics an underreporting pattern found in a novel linked data for Uruguay. Our simulations show that if one chooses a threshold that is not close to the true one, corrected inequality measures may be significantly biased. Interestingly, the bias using the replacing method is less sensitive to the choice of threshold. We approach the threshold selection challenge in practice using the Uruguayan linked data. Our findings are analogous to the simulation exercise. These results, however, should not be considered a general assessment of the two methods.     

A model of site-specific nutrient management

A model is introduced to answer three questions pertaining to site-specific nutrient management in production of orchard crops: which input factors of crop production are limiting yield; what action should be taken to remove the limiting factors; and what is the potential gain in revenue from taking the action. Our model captures the essence of the law of the minimum in that yield and revenue increase only if the limiting nutrients are adjusted. An example of pear trees shows how to implement the method.     

Security of property rights and transition in land use

Price and yield uncertainty are traditional considerations in agricultural markets and their impact on development. Agricultural producers in transition economies face an additional risk factor – changes in the institutional protection of property rights. This paper illustrates how institutional uncertainty may affect investment, land use, and crop mix patterns. In particular, in the Ukrainian example, the rights of tenants are viewed as uncertain in anticipation of establishment of an open market for sale of agricultural land. Establishment of the land market in Ukraine has been postponed several times over the last 15 years and a significant number of lease contracts are not formalized. A large panel of farm-level data was used to show that a higher share of rented land is associated with a lower share of land used for investment intensive perennial crops controlling for prices and other factors. The difference in response to uncertainty is found to be significant among three crop types: perennials, grains and oil crops. The implication is that the lower level of protection of use rights and uncertainty regarding the future regulation of land sales market lead to under-investments in more capital intensive crops. As a result, tenants deviate from the optimal crop mix, reducing the productivity of tenant farms. Farms under 200 ha are affected most negatively as they are less likely to be able to access the level of legal and political protection enjoyed by large farms.