A Banking Explanation of the US Velocity of Money: 1919-2004

The paper shows that US GDP velocity of M1 money has exhibited long cycles around a 1.25% per year upward trend, during the 1919-2004 period. It explains the velocity cycles through shocks constructed from a DSGE model and annual time series data (Ingram et al., 1994). Model velocity is stable along the balanced growth path, which features endogenous growth and decentralized banking that produces exchange credit. Positive shocks to credit productivity and money supply increase velocity, as money demand falls, while a positive goods productivity shock raises temporary output and velocity. The paper explains such velocity volatility at both business cycle and long run frequencies. With filtered velocity turning negative, starting during the 1930s and the 1987 crashes, and again around 2003, results suggest that the money and credit shocks appear to be more important for velocity during less stable times and the goods productivity shock more important during stable times.business cycle, credit shocks, velocity and volatility

US volatility cycles of output and inflation, 1919-2004: a money and banking approach to a puzzle

The post-1983 moderation coincided with an ahistorical divergence in the money aggregate growth and velocity volatilities away from the downward trending GDP and inflation volatilities. Using an endogenous growth monetary DSGE model, with micro-based banking production, enables a contrasting characterization of the two great volatility cycles over the historical period of 1919-2004, and enables this puzzle to be addressed more easily. The volatility divergence is explained by the upswing in the credit volatility that kept money supply variability from translating into inflation and GDP volatility

A banking explanation of the US velocity of money: 1919–2004

The paper shows that US GDP velocity of M1 money has exhibited long cycles around a 1.25% per year upward trend, during the 1919-2004 period. It explains the velocity cycles through shocks constructed from a DSGE model and annual time series data (Ingram et al., 1994). Model velocity is stable along the balanced growth path, which features endogenous growth and decentralized banking hat produces exchange credit. Positive shocks to credit productivity and money supply increase velocity, as money demand falls, while positive goods productivity shock raises temporary output and velocity. The paper explains such velocity volatility at both business cycle and long run frequencies. With filtered velocity turning negative, starting during the 1930s and the 1987 crashes, and again around 2003, results suggest that the money and credit shocks appear to be more important for velocity during less stable times and the goods productivity shock more important during stable times

Money velocity in an endogenous growth business cycle with credit shocks.

The explanation of velocity in neoclassical monetary business cycle models relies on a goods productivity shocks to mimic the data's procyclic velocity feature; money shocks are not important; and the financial sector plays no role. This paper sets the model within endogenous growth, adds exchange credit shocks, and finds that money and credit shocks explain much of the velocity variation. The role of the shocks varies across sub-periods in an intuitive fashion. Endogenous growth is key to the construction of the money and credit shocks since these have similar effects on velocity, but opposite effects upon growth. The model matches the data's average velocity and simulates most of the velocity volatility that is found in the data. Its underlying money demand is Cagan-like in its interest elasticity, so that money and credit shocks cause greater velocity variation the higher is the nominal interest rate

Short-term forecasting of GDP using large monthly datasets - a pseudo real-time forecast evaluation exercise

This paper evaluates different models for the short-term forecasting of real GDP growth in ten selected European countries and the euro area as a whole. Purely quarterly models are compared with models designed to exploit early releases of monthly indicators for the nowcast and forecast of quarterly GDP growth. Amongst the latter, we consider small bridge equations and forecast equations in which the bridging between monthly and quarterly data is achieved through a regression on factors extracted from large monthly datasets. The forecasting exercise is performed in a simulated real-time context, which takes account of publication lags in the individual series. In general, we find that models that exploit monthly information outperform models that use purely quarterly data and, amongst the former, factor models perform best. JEL Classification: E37, C53.Bridge models, Dynamic factor models, real-time data flow.

Credit shocks in a monetary business cycle

The paper sets out a monetary business cycle model extended to include the production of credit that serves as an alternative to money in transactions and is subject to productivity shocks. The model provides some improvement on certain puzzles, in particular by capturing the procyclic movements of monetary aggregates, inflation and interest rates. And its application to analyse banking episodes indicates that the credit shock helps explain cycle behavior during the US financial deregulation period of the 1980s and 1990

A Comparison of Exchange Economies within a Monetary Business Cycle

The paper sets out a monetary business cycle model with three alternative exchange technologies, the cash-only, shopping time, and credit production models. The goods productivity and money shocks a§ect all three models, while the credit model has in addition a credit productivity shock. The paper compares the performance of the models in explaining the puzzles of the monetary business cycle theory. The credit model improves the ability to explain the procyclic movement of monetary aggregates, ináation and the nominal interest rate

US volatility cycles of output and inflation, 1919-2004: a money and banking approach to a puzzle

The post-1983 moderation coincided with an ahistorical divergence in the money aggregate growth and velocity volatilities away from the downward trending GDP and inflation volatilities. Using an en dogenous growth monetary DSGE model, with micro-based banking production, enables a contrasting characterization of the two great volatility cycles over the historical period of 1919-2004, and enables this puzzle to be addressed more easily. The volatility divergence is explained by the upswing in the credit volatility that kept money supply variability from translating into inflation and GDP volatility

The analysis of the caponizing data of native Hungarian speckled chickens

Because of the spread of intensive poultry varieties and hybrids the indigenous varieties become endangered. Our old species are not compatible with the modern ones and cannot keep up with the industry-like economical production. For this reason, we must endeavour to preserve our old species and to keep their important characteristics that can be utilized for breeding later. Beside the gene preservation, we endeavour to find the best way for the production-purpose utilisation of our speckled chicken stocks. The experiment was designed to revive an old traditional method, the caponizing, to produce special products with culinary curiosities. In capon production experiments, two-year slaughtered values were compared. As a result, we can say the Hungarian old speckled chicken varieties are suitable to produce special and marketable products

Credit shocks in a monetary business cycle

The paper sets out a monetary business cycle model extended to include the production of credit that serves as an alternative to money in transactions and is subject to productivity shocks. The model provides some improvement on certain puzzles, in particular by capturing the procyclic movements of monetary aggregates, inflation and interest rates. And its application to analyse banking episodes indicates that the credit shock helps explain cycle behavior during the US financial deregulation period of the 1980s and 1990