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The purpose of this paper is to assess how direct payments (DPs) of the Common Agricultural Policy affect income and revenue variability faced by Italian farmers.

Balanced farm-level panel data are used to construct coefficients of variation over the period 2003-2012. Nonlinear robust regression techniques are used to measure the effect of DP, farm size, fixity in resources, labor intensity, farm production orientation, and specialization on the variability of farm income (FI) and farm revenue. This is done on the overall sample as well as on subsamples of farms located in different regions and belonging to different types of farming.

DPs have mixed effects on the variability of FI. While a negative and significant relationship is found on the whole national sample, this is not generally the case when models are run on the considered subsamples. On the contrary, DPs have always significant variability increasing effects on revenue. This suggests that DPs reduce the degree of risk that farmers face allowing them to engage in riskier activities. Thus, DPs are less effective than expected in terms of income stabilization because these distort farmers’ risk management behavior. Because of this, DPs could constrain the development of markets for risk management instruments and reduce the effectiveness of policies supporting the use of these instruments.

The analysis is inspired by El Benni et al. (2012) but uses a different approach, applies it to a different country, and yields different results. Volatility measures are calculated over more years, and the paper accounts for differences in farm production orientation and is not based on an unbalanced panel of farms. Because of these differences, the authors obtained different results regarding the correlation between DP and income and, even more, revenue variability. Finally, comparing the results of models referring to FI and farm revenue improves the author’s understanding of the impact of DP on farmers’ risk management behavior and allows interesting policy considerations.

The purpose of this paper is to identify the potential relationship between farm income variability and off-farm employment decisions in the short and medium term for the case of Irish farm operators.

Panel probit models of off-farm labour supply are estimated using Teagasc National Farm Survey data for Irish farms. The framework is based largely on standard expected utility but includes a constraint for recent employment history.

The analyses identifies some evidence of a positive association between farm income variability and off-farm employment in the medium term but no significant relationship in the short term. This suggests that off-farm employment is part of a wider portfolio decision but is not a strong solution to short-term farm income shocks.

European farmers increasingly face high income variability but financial risk management tools are not sufficiently developed or widely accessible to assist farmers in managing the associated risk. This deficiency can have negative implications for household economic welfare and future farm investments and hence the future farm income. Off-farm employment can form part of a wider medium-term portfolio strategy but more effective tools are also required for risk management particularly in dealing with short-term volatility and where off-farm employment is not a realistic endeavour given time constraints and/or demographics.

The estimation of farm income variability includes a detrending method thus reducing the likelihood of overestimating farm income variability for farms in deliberate expansion or decline. While previous research has typically focused on the short-term response of farmers to historical farm income variability, this research has distinguished between the short and medium term.

The purpose of this paper is to examine the factors affecting the relative variability in farm and off‐farm income for Canadian farm operators.

Variability of farm and off‐farm income is analyzed using a dataset of 17,000 farm operators from 2001 to 2006. Relative ranking of the coefficients of variation (CV) for farm and off‐farm income are compared across farm types and are regressed against factors conditioning the variations.

Greater reliance on farm income results in lower (greater) relative variability in farm (off‐farm) income. Larger commercial operations experience larger farm income volatility because they are less risk averse or they can manage more risk. Diversification and off‐farm employment appear to be risk management strategies for commercial operations.

Government payments have a small, positive effect on farm and off‐farm income variability, indicating this support leads farmers to take on more risky activities and/or reduce the use of self‐insurance activities. Results could also be due to the lag between the time of the income reduction and the time in which the aid is received. Further research is necessary to decipher the effects of government support on farm decisions.

The results on relative variation in the farm and off‐farm income across farm type raises questions about whether government programs should target specific operations.

While income variation remains a focus of public policy, factors affecting its variability are not well‐understood. Studies have examined the level of farm income and the decision to participate in off‐farm employment but none has examined the variance in both income sources.

Purpose: The paper analyzes the variability of labor incomes in Argentina from mid-1980s to 2005. The magnitude of income instability and its determinants are evaluated under different macroeconomic contexts. It also analyzes how income fluctuations have influenced income distribution. Finally, the income convergence hypothesis is explored.

Methodology/approach: Different quantitative procedures are employed to measure mobility from dynamic information coming from the regular household survey. Four periods are distinguished that are relatively homogeneous. Dynamic pseudo-panels are also considered.

Findings: The growth in occupational instability registered since the mid-1990s led to a high variability of incomes despite the macroeconomic stability enjoyed throughout the nineties. Moreover, the panorama of growing inequality in the distribution of monthly income (the usual measure employed in Argentina) is also appropriate to describe what happened with the changes in the distribution of more permanent incomes. Finally, long-term income mobility in Argentina is scarce, indicating that the income path does not converge to the general mean.

Research limitations/implications (if applicable): Data refer only to Greater Buenos Aires since microdata are not available for the other areas covered by survey for the entire period under analysis. However, results are reasonably representative of the whole urban areas of the country.

Originality/value of paper: This research identifies the relative importance of labor market and macroeconomic factors in explaining income mobility. Moreover, it is for the first time in Argentina that dynamic information coming from panel data and pseudo-panels are analyzed together.

The purpose of this study is to examine the effects of agricultural policy reform – specifically the change from market to direct payment support – on income variability of Swiss farming households. In addition, the observed heterogeneity in income risks across farms and time is explained in terms of farm and regional characteristics.

Unbalanced farm‐level panel data of the Swiss farm accountancy network (FADN) are used to construct coefficients of variation of five‐year overlapping time intervals for total household income and gross farm revenues over the period 1992 to 2009. Linear fixed effect models are applied to measure the effect of specialization, off‐farm income, direct payments, farm size, and liquidity on the variability of gross farm revenues and household income in the valley, hill, and mountain regions.

The switch from market‐based support to direct payments has decreased the variability of farm revenues and household income. The strong reliance on direct payments serves as insurance for most farmers and reduces both household income and revenue risk. Off‐farm income can be used by farmers to reduce household income risk but it increases revenue risk in the valley regions. In all of the regions considered, farm size has a positive effect on household income risk and a negative effect on revenue risk. A high degree of specialization increases both gross revenue and household income risk. Potential revenue insurance contracts should specify farmers' off‐farm employment, the degree of specialization, farm size, and regional specific risk profiles.

This paper assesses the complementary effects of specific farm characteristics and risk management strategies with regard to both farm revenue and household income risk. Influences of agricultural policy changes on income risks are also empirically assessed at different spatial scales.

For many farm families and operators across the OECD countries, off‐farm income has become a major determinant of their well‐being. The purpose of this paper is to investigate the potential role of off‐farm employment as a risk management tool among farm operators.

A two‐part model is applied to a longitudinal farm‐level data set for about 20,000 Canadian farms, from 2001 to 2006, in order to estimate the relationship between farm income risk and the decision to participate in the off‐farm labor market and the level of off‐farm employment income.

The variability of farm market revenue is found to be positively related to the likelihood of off‐farm work and the level of off‐farm employment income, in particular for operators of relatively large farms. Hence, farm operators' production decisions appear to be conditioned on an income portfolio that includes a substantial amount of off‐farm income for all sizes of farms.

These results reinforce the need to consider the portfolio effect induced by the integration of farm resources within the non‐farm sector. This is particularly relevant to risk management farm policies that have typically considered decisions made in the agricultural sector in isolation.

This paper uses a true farm‐level panel data set to investigate the relationship between farm income risk and off‐farm work. The size of the data set also allows the robustness of the results across farm typologies and size to be tested. This study contributes to the understanding of structural changes in the farm sector, and their potential implications for both rural and agricultural policies.

The purpose of this paper is to empirically investigate the effects of farm income variability, farm size, and other socio‐demographic characteristics on the precautionary saving behavior of farm households and to estimate the influences of the identified factors on the amount of savings by self‐employed farm households.

Using 2003 Agricultural Resource Management Survey (ARMS) data and a Double‐Hurdle procedure, the likelihood and the amount of savings by farm households are estimated.

An important empirical finding of this study is that variability in income plays an important role in explaining precautionary savings of US farm households. Findings suggest that farm households facing higher income risk save more and accumulate more wealth. It is indicated that several farm, operator, household, and demographic attributes contribute to the precautionary savings of farm households. In particular, results show that educational attainment by operator and spouses have positive impact on the decision to save. In addition, results from this study show that farms that specialize in cash grain are likely to have precautionary savings.

Farm households today are virtually indistinguishable from non‐farm households in their levels of income and diversity of employment. As a result, government policies that influence general economic conditions have much more profound impacts on farm families. Federal support of farm income warrants continued scrutiny. This paper shows that greater income uncertainty increases savings and wealth of farm households. Therefore, farm policies that reduce income variability or uncertainty will have an impact on precautionary savings and wealth of farm households.

Several studies have investigated savings of households; however, these studies are limited to entire US population, older Americans, or non‐self‐employed individuals in the USA. Little is known about the savings behavior of self‐employed US farm households owing to a lack of household survey data and because of the complex relationship between the farm household and farm business in terms of resource allocation (both capital and labor).

The purpose of this paper is to examine empirically the nature of smoothing returns practices in a sample of 79 Islamic banks across 19 countries during the period 2001‐2006.

Previous researchers' methods, based on the variation and determination coefficients, are used in this study to detect the smoothing practices.

Results indicate that the revenues from the “Shariah‐based products” derived from the profit and loss sharing principle show higher variability than the “Shariah compliant revenues” and that income from this source is relatively lower. They also show that a large number of Islamic banks engage in natural income smoothing. Based on the determination coefficient results, 70 per cent of banks were found to have less smoothed total revenue than their net income. Results based on variation coefficient further confirm this finding, with 67 banks having a coefficient of total revenue higher than that of the net income.

The results suggest that Islamic banks should strengthen the use of smoothing techniques, such as the profit equalization reserves (PER) and the investment risk reserves (IRR), as they allow them to further stabilize the revenues payout for the investment account holders (IAH) and therefore mitigate withdrawal risk. Standardizing the smoothing techniques could be a solution to overcome the variability of this category of revenue.

This work is the first of its kind for Islamic banks. It extends previous research by examining whether or not managers may smooth their results naturally or intentionally. It also helped to bridge the gap in the literature by providing the empirical evidence on the smoothing returns in Islamic finance.

The purpose of this paper is to examine empirically whether corporate governance mechanisms have an effect on income‐smoothing behavior in the People's Republic of China.

The sample comprises 1,358 companies listed in the Shanghai Stock Exchange and the Shenzhen Stock Market during the period 1999 to 2006. By comparing the variability of income to the variability of sales, an income smoother can be identified if income is less variable than sales.

The authors' empirical results show that income smoothing is more severe when the state is the controlling shareholder of the Chinese listed firm. Firms with more independent directors are more likely to engage in income smoothing. The governance mechanisms such as board of directors, supervisory board, audit committee, external auditors, and shareholders' participation are not effective in curtailing income smoothing in China.

For Chinese firms and especially government‐linked enterprises, the way in which they present themselves may be significant, since the image they present to potential strategic partners may be marred by suspicions of income smoothing.

The paper presents the current development of China's corporate governance system and indicates that agency conflicts between controlling shareholders and minority investors account for a significant portion of earnings management in China.

Building on the risk balancing theory and on recent discussions the appropriateness of using farm income maximization as behavioural assumption, this paper extends the risk balancing framework by accounting for business-household interactions. The purpose of this paper is to theoretically introduce the concept of farm household risk balancing, a theoretical framework in which the farm household sets a constraint on the total household-level risk and balances farm-level and off-farm-level risk.

The paper argues that the risk behaviour of farmers is better understood by considering risk at the household level. Using an analytical framework, equations are derived linking the farm activities, off-farm activities, consumption and business and private liquidity.

The framework shows that a farm household that wants to minimize the risk that total household cash flow falls below consumption needs, may exhibit a wide variety of behavioural responses to changes in the policy and economic environment.

The framework suggests multiple ways for policy makers and individual farmers to support risk management.

Risk management is at the core of the agricultural policy and it is of paramount importance to be able to understand behavioural responses to market and policy instruments. This paper contributes to that by suggesting that the focus of current risk analysis and management studies may be too narrowly focused at the farm level.