One of the most important objectives of economic policy is to ensure, via the appropriate manipulation of the available policy instruments (control variables), that the economic system tracks, as closely as possible, a desired path for the policy targets (outputs). One of the approaches that has been utilized for the design of economic policy is the feedback approach, stemming from the mathematical control theory literature. Various aspects of the feedback methodology have been utilized for the purposes of policy design for more than 50 years, starting with the use of PID controllers in the seminal paper by Phillips (1954). These aspects range from (stochastic) optimal feedback control (see, The importance of feedback rules for policy design is evident from the fact that for more than 20 years monetary policy decisions have been, to a large extent, based on the Taylor rule (see Taylor 1993); this is a linear feedback policy rule stipulating (in its simplest form) that the interest rate is set based on deviations of inflation and GDP from target levels of inflation and potential GDP, respectively. It is interesting to note here that Taylor presented a rule that had fixed settings for the parameters; in particular:among(1) r = p + 0.5y + 0.5(p − 2) + 2
AbstractWe present an algorithmic approach for the design of fiscal policy rules. In particular, using algorithmic feedback control techniques, we design linear feedback policy rules such that predetermined target levels for GDP and public debt are simultaneously, exactly tracked. We run a number of simulations in order to examine the effects of different policy response rates and the overall effectiveness of the proposed methodology.