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Research with Keynesian-style models has emphasized the importance of the output gap for policies aimed at controlling inflation while declaring monetary aggregates largely irrelevant. Critics, however, have argued that these models need to be modified to account for observed money growth and inflation trends, and that monetary trends may serve as a useful cross-check for monetary policy. We identify an important source of monetary trends in form of persistent central bank misperceptions regarding potential output. Simulations with historical output gap estimates indicate that such misperceptions may induce persistent errors in monetary policy and sustained trends in money growth and inflation. If interest rate prescriptions derived from Keynesian-style models are augmented with a cross-check against money-based estimates of trend inflation, inflation control is improved substantially.
Modern macroeconomics empirically addresses economy-wide incentives behind economic actions by using insights from the way a single representative household would behave. This analytical approach requires that incentives of the poor and the rich are strictly aligned. In empirical analysis a challenging complication is that consumer and income data are typically available at the household level, and individuals living in multimember households have the potential to share goods within the household. The analytical approach of modern macroeconomics would require that intra-household sharing is also strictly aligned across the rich and the poor. Here we have designed a survey method that allows the testing of this stringent property of intra-household sharing and find that it holds: once expenditures for basic needs are subtracted from disposable household income, household-size economies implied by the remainder household incomes are the same for the rich and the poor.
We analyze incentives for loan officers in a model with hidden action, limited liability and truth-telling constraints under the assumption that the principal has private information from an automatic scoring system. First we show that the truth-telling problem reduces the bank’s expected profit whenever the loan officer cannot only conceal bad types, but can also falsely report bad types. Second, we investigate whether the bank should reveal her private information to the agent. We show that this depends on the percentage of good loans in the population and on the signal’s informativeness. Though we had to define different regions for different parameters, we concluded that it might often be favorable to not reveal the signal. This contradicts current practice.