Inflation Forecast Targeting in an Overlapping Generations Model

In the framework of a standard overlapping generations model, it is shown that active inflation forecast targeting reinforces mechanisms that lead to indeterminacy of the monetary steady state and to countercyclical behavior of young-age consumption. The inflation forecast targeting rule which minimizes the volatility of inflation can be active or passive, depending on the characteristics of shocks and the risk aversion of households. Inflation forecast errors are always greater under active inflation forecast targeting than under passive inflation forecast targeting or strict money growth targeting. The monetary steady state is more likely to be indeterminate under an active rule of inflation forecast targeting than under the corresponding backward-looking rule (inflation targeting), but backward-looking rules can render the monetary steady state unstable.Monetary policy, Inflation forecast targeting, Overlapping generations model

Discriminated Belief Propagation

Near optimal decoding of good error control codes is generally a difficult task. However, for a certain type of (sufficiently) good codes an efficient decoding algorithm with near optimal performance exists. These codes are defined via a combination of constituent codes with low complexity trellis representations. Their decoding algorithm is an instance of (loopy) belief propagation and is based on an iterative transfer of constituent beliefs. The beliefs are thereby given by the symbol probabilities computed in the constituent trellises. Even though weak constituent codes are employed close to optimal performance is obtained, i.e., the encoder/decoder pair (almost) achieves the information theoretic capacity. However, (loopy) belief propagation only performs well for a rather specific set of codes, which limits its applicability. In this paper a generalisation of iterative decoding is presented. It is proposed to transfer more values than just the constituent beliefs. This is achieved by the transfer of beliefs obtained by independently investigating parts of the code space. This leads to the concept of discriminators, which are used to improve the decoder resolution within certain areas and defines discriminated symbol beliefs. It is shown that these beliefs approximate the overall symbol probabilities. This leads to an iteration rule that (below channel capacity) typically only admits the solution of the overall decoding problem. Via a Gauss approximation a low complexity version of this algorithm is derived. Moreover, the approach may then be applied to a wide range of channel maps without significant complexity increase

Time-consistent Monetary Policy Rules

A monetary policy rule is a function mapping any given output level of the economy to a corresponding rate of inflation. Such a rule is time-consistent if the central bank has no incentive to deviate from it. Within a simple dynamic model combining an output-inflation trade-off with rational private-sector expectations we study existence and properties of time-consistent monetary policy rules. It is shown that such rules exist only if (i) the central bank gives relatively high weight to price stability and relatively low weight to output stabilization and if (ii) the random shocks to the economy are not too strong. If time-consistent monetary policy rules exist, they are generically non-unique.Monetary policy, Time-consistency, Policy rules, Inflation

some notes on discount factor restrictions for dynamic optimization problems

We consider dynamic optimization problems on one-dimensional state spaces. Un- der standard smoothness and convexity assumptions, the optimal solutions are characterized by an optimal policy function h mapping the state space into itself. There exists an extensive literature on the relation between the size of the discount factor of the dynamic optimization problem on the one hand and the properties of the dynamical system xt+1 = h(xt) on the other hand. The purpose of this paper is to survey some of the most important contributions of this literature and to modify or improve them in various directions. We deal in particular with the topological entropy of the dynamical system, with its Lyapunov exponents, and with its periodic orbits.

Hirarchical Growth: Basic and Applied Research

We develop a model that incorporates salient features of growth in modern economies. We combine the expanding-variety growth model through horizontal innovations with a hierarchy of basic and applied research. The former extends the knowledge base, while the latter commercializes it. Two-way spillovers reinforce the productivity of research in each sector. We establish the existence of balanced growth paths. Along such paths the stock of ideas and the stock of commercialized blueprints for intermediate goods grow with the same rate. Basic research is a necessary and sufficient condition for economic growth. We show that there can be two different facets of growth in the economy. First, growth may be entirely shaped by investments in basic research if applied research operates at the knowledge frontier. Second, long-run growth may be shaped by both basic and applied research and growth can be further stimulated by research subsidies. We illustrate different types of growth processes by examples and polar cases when only upward or downward spillovers between basic and applied research are present.