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T.Kussaiynov, Professor, Phd, Specialist in the Field of Economy. Address: Astana, Pr

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T.Kussaiynov, Professor, Phd, Specialist in the Field of Economy. Address: Astana, Pr Systemic risk and government participation in crop insurance T.Kussaiynov, Professor, Doctor of Economic Sciences S. Seifullin Kazakh Agro Technical University, Astana __________________________________________________________________________________ TALGAT A.KUSSAIYNOV: Systemic risk and government participation in crop insurance Abstract Each agricultural system (region, rayon, and farm) has its own distinctive systemic risk degree that can be measured with use of beta-coefficient. Beta-coefficient is a measurement of non-diversifiable risk. For an agricultural system beta-factor is useful when assessing systemic risk and understanding type of reaction of crop yield onto systemic risk. Key words: agriculture, systemic risk, insurance, beta-coefficient, grain production, premium rate __________________________________________________________________________________ Introduction Agriculture insurance as a key risk management instruments is supported by the government in order to raise the efficiency of resource use and keep up the agriculture income sustainability. Additionally, government participation in risk management can be explained by its concerns of country food security for catastrophic risks may lead to unacceptable dependence on food import. The chief factor for government participation in financing the crop insurance is the existence of systemic risk in the sector. For the nature and climatic differences that are inherent to agricultural production in vast areas in Kazakhstan different farming systems are subject to systemic risk in different degrees. This situation makes to differentiate the government crop insurance subsidies in accordance with natural and climatic conditions of regions and rayons. So the analysis of state and public funds implication for crop insurance financing should get started from systemic risk assessment. Income volatility as well as yields unsteadiness depends on a range of factors which may be classified in two groups: controllable and uncontrollable ones. Systemic risk assessment in agriculture produces adequate results if they are based on the analysis of statistic properties of uncontrollable factors. Contact address: T.Kussaiynov, Professor, PhD, specialist in the field of economy. Address: Astana, pr. Pobedy, 62. [email protected] Systemic risk ( I ) may be calculated as a ratio of gross harvest volatility ( R1 ) in an overall farming system to its volatility ( R2 ) calculated for the hypothetical situation when harvest volatilities in different subsystems are mutually independent, that is R I 1 100 (1) R2 In so doing, harvest volatility rates R1 и R2 are calculated in the following way: V R1 (2) Cср Vi R2 , (3) Cср where V - harvest volatility in an overall farming system, Vi – harvest volatility over subsystems, Cср – Science Review, Volume I (7) – Astana, 2011 – P. 65-68 average harvest in an overall farming system. If I >1 then systemic risk exists; systemic risk is absent when I =1. Calculations done with use of formulae (1) - (3) over grain producing region of Kazakhstan (Akmola, Kostanai, North-Kazakhstan oblasts) show that the share of systemic risk reaches up to 38%; respectively, idiosyncratic (diversifiable) risk forms 62% of total risk. As data get aggregated, the differences between farming systems become less tangible. So, the risk assessment should be done at the rayons level as well if we seek for more accurate results. Calculations over 17 regions of Akmola oblast demonstrate the presence of systemic risk in the grain sector of the oblast. Systemic risk accounts for 73,3% of total risk as the share of individual risk makes up 26,7%. So, it is clear that at the lower hierarchy level systemic risk shows up stronger. Grain yields variability in the main grain producing oblasts – Akmola, Kostanai, and North- Kazakhstan – is high, the variability coefficient gets up to 0,30. Moreover, there are different natural and economic conditions in each oblast. So, we have to assess the volatility of grain yields at the rayon level in order to get more precise conception. Chief cereals – wheat yield variability calculations over regions of Akmola oblast indicate significantly different variability coefficients. Most regions show variability coefficients ranging from 0,30 to 0,45 with an average of 0,37. At the moment, mandatory crop insurance system is in work in Kazakhstan in accordance with so called “Law on Mandatory Crop Insurance” passed in 2004. Premium rates are calculated and set by the Government. And premium rates are unified for an oblast or set of oblasts. But, our calculations indicate that premium rates in crop insurance should be differentiated at rayon level at least; better to calculate the premium rate for each farm individually. Only farms with higher liability to risk benefit from unified premium rates, whereas farms with low liability to risk have no advantages from participation in such an insurance program. While using the unified premium rates in Akmola oblast conditions, one should expect that in fact farms of Shchuchinsk, Sandyktau, Arshaly, Zerendy and some other regions with more sustainable yields would subsidize (through insurance premiums) the farms of Zharkain, Astrakhan, Enbekshilder and some regions with less sustainable grain yields. Each agricultural system (region, rayon, and farm) has its own distinctive systemic risk degree that can be measured with use of beta-coefficient. Beta-coefficient is a measurement of non-diversifiable risk. For an agricultural system beta- factor is useful when assessing systemic risk and understanding type of reaction of crop yield onto systemic risk. If farm beta-coefficient appears to be positive, then yield increase in a region means yield increase on the farm as well. And vice versa, region yield decrease implies the farm yield reduction, so in that systemic risk lies. When we deal with negative beta-coefficient farm yield increase is accompanied with region yield reduction, and vice versa. Beta-coefficient is measured with the following equation: yt ( yrt ), where yt farm yield in a year t ; constant; beta-coefficient; yrt region yield in a year t . Coefficient of determination R2 measures explanatory capability of the equation. It can be interpreted as a share of systemic risk in the overall risk that manifests itself in an yield variability. Respectively, the difference between 1 and R2 is the share of an individual risk in the overall risk. In the table 1 there are beta-coefficients over rayons of Akmola oblast calculated with respect to average oblast wheat yield. The last two columns reflect the shares of systemic and individual risks over rayons respectively. Table 1 – Wheat yield beta-coefficients over rayons of Akmola oblast № Rayon Beta-coefficient Share of systemic Share of risk (R2) individual risk (1- R2) 1 Akkol 1,04 0,86 0,14 2 Аrshaly 0,56 0,73 0,27 3 Аstrakhan 0,86 0,91 0,09 4 Аtbasar 0,89 0,93 0,07 5 Bulandy 0,82 0,72 0,28 6 Egindykol 0,8 0,88 0,12 7 Enbekshilder 1,53 0,74 0,26 8 Еreymentau 0,85 0,65 0,35 9 Еssil 0,75 0,9 0,1 10 Zhaksy 0,98 0,87 0,13 11 Zharkain 0,76 0,77 0,23 12 Zerendy 1,02 0,71 0,29 13 Кorgalzhyn 0,63 0,85 0,15 14 Sandyktau 0,95 0,79 0,21 15 Tselinograd 0,68 0,89 0,11 16 Shortandy 0,98 0,93 0,07 17 Shchuchinsk 0,83 0,63 0,37 Akmola oblast 1 - - Systemic risk is not subject to insurance with use of market instruments. So it is inevitable to identify and measure that kind of risk. Identification of losses caused by systemic risk is of great importance when determining the degree of government participation in compensation of losses caused by nature disasters. Assessment of losses brought to agricultural entrepreneurs by systemic risk may be done with use of beta-coefficient. Yield loss for systemic risk should be calculated in the following way: i i (yмо yф ) , где i - crop beta-coefficient on the farm i ; yмо - average regional crop yield; yф - actual regional crop yield in a year under consideration. In so doing, one should keep in a view that: a) yмо yф for i 0 ; b) yмо yф for i 0 . Remark (a) corresponds to a case when regional yield and farm yield change on the same direction, that is, beta-coefficient is positive. Yield loss for systemic risk on the farm takes place if only actual regional yield appears to be less than the average one. Remark (a) corresponds to a case, when regional yield and farm yield change on the opposite direction, that is, beta-coefficient is negative. Yield loss for systemic risk on the farm takes place if only actual regional yield appears to be above the average one. For instance, when a farm wheat yield beta-coefficient equals 1,5, and the regional yield average is equivalent to 12 c/ha, whereas actual regional yield in the year under consideration makes up 10 c/ha, then the farm loss for systemic risk corresponds to 1,5 (12 10) 3 c/ha. If the government takes responsibility to indemnify for a loss made by systemic risk then it should pay an indemnity equivalent to 3 c/ha (in case of 100% indemnity). In case of, for example, 75% indemnity, the loss to be compensated equals 2,25 c/ha ( 0,75 0,75 3 2,25 ). In the table 2 there are estimates of wheat loss for the systemic risk over regions of Akmola oblast (with the average yield of 10,4 c/ha). Table 2 – Loss estimates over regions of Akmola oblast (example) № Rayon Actual rayon yield, Beta- Loss for c/ha1 systemic coefficient i risk i , c/ha 1 Akkol 8,00 1,04 0,94 2 Аrshaly 7,10 0,56 0,50 3 Аstrakhan 9,60 0,86 0,77 4 Аtbasar 9,70 0,89 0,80 5 Bulandy 11,10 0,82 0,74 6 Egindykol 6,80 0,8 0,72 7 Enbekshilder 12,00 1,53 1,38 8 Еreymentau 5,10 0,85 0,77 9 Еssil 8,20 0,75 0,68 10 Zhaksy 10,10 0,98 0,88 11 Zharkain 7,40 0,76 0,68 12 Zerendy 13,20 1,02 0,92 13 Кorgalzhyn 4,20 0,63 0,57 14 Sandyktau 13,00 0,95 0,86 15 Tselinograd 7,50 0,68 0,61 16 Shortandy 10,10 0,98 0,88 17 Shchuchinsk 14,10 0,83 0,75 Akmola oblast 9,50 1 0,90 In the table 2, the last column shows the size of indemnity (expressed in centners of the wheat per hectar).
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