No abstract

In modern conditions of economic development, agricultural organizations are faced with the need to manage their property and obligations in situations of risk and uncertainty. Accounting and analytical support is becoming an important source of information for making effective management decisions. An important stage of management at all levels is control. Effective control is not possible without consideration and analysis, which causes certain difficulties. The risk management system works with all identified risks of the organization. The accounting system covers a limited number of risks with the necessary parameters for their registration and acceptance for accounting. When registering risk, each type of accounting (financial, management, tax, statistical) is determined by its goals, uses different methods of assessment, etc. The reporting in each case meets specific criteria. Differences in the principles of accounting and assessment of one risk in several accounting systems cause difficulties in the practice of risk management. The risk management process has its own procedure regulated by international and national standards for risk management, which do not contain unified actions regarding further accounting measures for identified risks. This leads to a decrease in the quality of information regarding risks to ensure control and management procedures. At the same time, accounting standards do not provide for management actions for risks accepted for accounting. This paper is devoted to the study of the role of accounting and analytical aspects in the risk management of agricultural organizations from the position of coordination of control actions of risk management and accounting procedures. General scientific methods were used in the study: a systematic approach, comparative analysis, logical generalization, modeling, etc.

No abstract

I study the effect of task difficulty on workers' effort and compare it to the effect of monetary rewards in an incentivized lab experiment. I find that task difficulty has an inverse-U effect on effort, and that this effect is quantitatively large when compared to the effect of conditional monetary rewards. Difficulty acts as a mediator of monetary rewards: conditional rewards are most effective at the intermediate or high levels of difficulty. I show that the inverse-U pattern of effort response to difficulty is not consistent with the Expected Utility model but is consistent with the Rank-Dependent Utility model that allows for non-linear probability weighting. I structurally estimate the model and find that it successfully captures the treatment effects observed in the data. I discuss the implications of my findings for the design of optimal incentive schemes for workers and modeling effort.

This paper contributes to the theory of average rate of change (ARC) measurement. The contribution is twofold. First, it relates ARC measurement to intertemporal choice. We show that an ARC of a variable can be identified with a discount rate which makes an economic agent indifferent between the initial and final temporal states of the variable. Furthermore, there is a one-to-one correspondence between ARC measures and one-parameter families of time preferences indexed by a discount rate. Second, we employ an axiomatic approach to generalize the conventional ARC measures (such as the difference quotient and the continuously compounded growth rate) in several directions: to variables with arbitrary connected domains, to not necessarily time-shift invariant dependence on dates, to sets of time points other than an interval, to a benchmark-based evaluation. The generalized ARC measures turn out to correspond to the existing time preference models such as the discounted utility and the relative discounting model of Ok and Masatlioglu [