Unemployment,income distribution and debt-financed investment in a growth cycle model

As recent experience suggests, the most significant economic fluctuations are those that combine real and financial factors. This paper works out a simple model that couples a version of Goodwin׳s (1967) growth cycle model of real fluctuations with insights drawn from a model of financial fluctuations based on Minsky׳s financial instability hypothesis (Vercelli, 2000, Sordi and Vercelli, 2006, Sordi and Vercelli, 2012). The model suggested substantially modifies that of Keen (1995), who combined insights from Goodwin and Minsky within a model of fluctuating growth. In the real part of the model we introduce the possibility of disequilibrium in the goods market and formalize a mechanism of output adjustment based on the conventional dynamic multiplier. The model so obtained may exhibit persistent dynamics and provide insights to enable better understanding of the nature of real-world fluctuations.     

PRICE AND QUANTITY RESPONSES TO COST AND DEMAND SHOCKS*

ABSTRACT When prices are inflexible, real variables like production and inventories must bear the brunt of responding to cost and demand shocks. In these circumstances, one expects to observe rather more variation in quantities than in prices, and that is, in fact, what we observe in the data. To explain this observation, one must explain why prices are inflexible. Our goal in this paper is to ascertain whether it is selectivity in response to demand shocks or just a more extensive smoothing of prices than quantities which accounts for the relatively higher variation in quantities which we observe. We conclude that selectivity in response is clearly evident in the data: demand shocks have only very weak effects on prices, but they have substantial (if rather transitory) effects on quantities.     

Risk shocks and housing supply: A quantitative analysis

This paper analyzes the role of stochastic uncertainty in a multi-sector housing model with financial frictions. We include time varying uncertainty (i.e. risk shocks) in the technology shocks that affect housing production and provide estimates of the time-series properties of risk shocks by using firm level productivity data. The analysis demonstrates that risk shocks to the housing production sector are a quantitatively important impulse mechanism for understanding housing price movements. Specifically, the model can match the volatility of housing prices observed in the data. It is also demonstrated that adjustment costs are important in replicating the contemporaneous correlation of housing prices with GDP and residential investment. Critically, bankruptcy costs act as an endogenous markup factor in housing prices and are an important determinant of house price volatility. However, in comparison to housing demand shocks, risk shocks have low explanatory power for real quantities.     

What determines the long-term correlation between oil prices and exchange rates?

In this study, we obtain the long-term correlation between oil prices and exchange rates by employing the dynamic conditional correlation-mixed data sampling (DCC-MIDAS) model. We then identify the factors that influence the long-term correlation using panel data analysis. We find that the long-run correlations between oil prices and exchange rates are negative for all oil-exchange rate markets except Japan. We also find that both inflation and term spread have negative effects, while the risk-free interest rate has a positive effect on the long-term correlation between oil prices and exchange rates. Importantly, the empirical results show that an increase in inflation will significantly damage the real value of the currency itself.     

A spatio-temporal model of house prices in the USA

This paper provides an empirical analysis of changes in real house prices in the USA using State level data. It examines the extent to which real house prices at the State level are driven by fundamentals such as real per capita disposable income, as well as by common shocks, and determines the speed of adjustment of real house prices to macroeconomic and local disturbances. We take explicit account of both cross-sectional dependence and heterogeneity. This allows us to find a cointegrating relationship between real house prices and real per capita incomes with coefficients (1,−1)$(1,-1)$, as predicted by the theory. We are also able to identify a significant negative effect for a net borrowing cost variable, and a significant positive effect for the State level population growth on changes in real house prices. Using this model we then examine the role of spatial factors, in particular, the effect of contiguous states by use of a weighting matrix. We are able to identify a significant spatial effect, even after controlling for State specific real incomes, and allowing for a number of unobserved common factors. We do, however, find evidence of departures from long run equilibrium in the housing markets in a number of States notably California, New York, Massachusetts, and to a lesser extent Connecticut, Rhode Island, Oregon and Washington State.     

Nonlinear adjustment,purchasing power parity and the role of nominal exchange rates and prices

Although the literature on purchasing power parity (PPP) is rich in controversy, the relative contribution of prices and nominal exchange rates to real exchange rate movements which restore PPP disequilibria has rarely been put under any close scrutiny. This paper as a first step applies a cointegrated VAR framework to test for stationary real exchange rates and linear adjustments in prices and nominal exchange rates. As a second step, ESTR error correction models are fitted to test whether nonlinear error correctional behaviour characterizes the data. The results clearly indicate that the nominal exchange rate is responsible for the nonlinear mean reverting behaviour in real exchange rates and also mainly drives overall adjustment. Applying dynamic stochastic simulations based on the estimated models, this study also confirms recent results that the half-life times of real exchange rate shocks are significantly smaller than the consensus benchmark of 3–5 years.     

Forecasting crude oil prices with DSGE models

In this study, we conducted an oil prices forecasting competition among a set of structural models, including vector autoregression and dynamic stochastic general equilibrium (DSGE) models. Our results highlight two principles. First, forecasts should exploit the fact that real oil prices are mean reverting over long horizons. Second, models should not replicate the high volatility of the oil prices observed in samples. By following these principles, we show that an oil sector DSGE model performs much better at real oil price forecasting than random walk or vector autoregression.     

A link between random coefficient autoregressive models and some agent based models

An agent based model (ABM), where each agent makes decisions by using the sum of two signals, is proposed. The first is related to the fundamental information while the second comes from trader’s idiosyncratic noise. This model entails the switching between two groups called fundamentalist and noise traders. Additionally, if the price impact function is log-linear, then the dynamic of log asset prices belongs to the class of random coefficient autoregressive RCA(p) models, which are known to share important stylized facts of financial prices.     

What (really) accounts for the fall in hours after a technology shock?

The paper asks how state of the art DSGE models that account for the conditional response of hours following a positive neutral technology shock compare in a marginal likelihood race. To that end we construct and estimate several competing small-scale DSGE models that extend the standard real business cycle model. In particular, we identify from the literature six different hypotheses that generate the empirically observed decline in hours worked after a positive technology shock. These models alternatively exhibit (i) sticky prices; (ii) firm entry and exit with time to build; (iii) habit in consumption and costly adjustment of investment; (iv) persistence in the permanent technology shocks; (v) labor market friction with procyclical hiring costs; and (vi) Leontief production function with labor-saving technology shocks. In terms of model posterior probabilities, impulse responses, and autocorrelations, the model favored is the one that exhibits habit formation in consumption and investment adjustment costs. A robustness test shows that the sticky price model becomes as competitive as the habit formation and costly adjustment of investment model when sticky wages are included.     

Bubble trouble ‐ are British house prices significantly overvalued?

The OECD last December said British house prices were overvalued by 30% or more. There has been much talk, including in a 2005 speech by Gordon Brown, of a house price bubble. This article, by Gavin Cameron, John Muellbauer and Anthony Murphy of Oxford University, finds no significant evidence for a bubble from a dynamic panel data model of British regional house prices between 1972 and 2003. The model consists of a system of inverted housing demand equations, incorporating spatial interactions and lags and relevant spatial parameter heterogeneity. The results are data consistent, with plausible long-run solutions and include a full range of explanatory variables. Novel features of the model include transaction cost effects influencing the speed of adjustment and housing market flows, as well as stocks, driving prices. Furthermore, the model allows for shifts in real and nominal interest rate effects as credit markets liberalised.     

货币政策和居民收入对房价影响的实证分析

近年来,房地产价格持续快速增长,影响房价的因素有很多,文章以辽宁省为例,建立贷款利率、货币供应量、城镇居民可支配收入和房屋销售价格的VAR模型,进行实证研究。利用EVIEWS7.0软件对模型进行脉冲响应函数和方差分解分析,得出贷款利率、货币供应量和居民可支配收入均对房价产生正向影响,并且居民可支配收入的贡献度最强,五年以上贷款利率贡献度最弱。     

FLEXIBLE ACCELERATOR ECONOMIC SYSTEMS AS COUPLED OSCILLATORS

Abstract In this paper, the capacity of a particular type of a formal theoretical model to generate‐compute non‐trivial economic dynamics is studied. The model chosen is the flexible accelerator and the classification of the attractors is made in terms of Wolfram four classes. The model at the origins of mathematical business cycle theories ( Frisch, 1933 ) generates class 1 limit points. The model by Goodwin (1951) generates class 2 limit cycles. We construct a class 3 basin of attraction, strange attractors, by coupling through trade variants of the oscillators present in Goodwin (1951) . It is shown that coupled oscillators may generate non‐stochastic irregular dynamic behaviours of the Goodwin (1946) type. The irregularity is shown through the computation of very rugged devil staircases. Whether the system of coupled nonlinear oscillators presented here belong to the class 4 type is still an open question. The analogy with the system of coupled oscillators and the well‐known Fermi–Pasta–Ulam experiment is also explored.     

ECONOMETRIC MODELS OF ASYMMETRIC PRICE TRANSMISSION

Abstract In this paper, we review the existing empirical literature on price asymmetries in commodities, providing a way to classify and compare different studies that are highly heterogeneous in terms of econometric models, type of asymmetries and empirical findings. Relative to the previous literature, this paper is novel in several respects. First, it presents a detailed and updated survey of the existing empirical contributions on price asymmetries in the transmission mechanism linking input prices to output prices. Second, this paper presents an extension of the traditional distinction between long‐run and short‐run asymmetries to new categories of asymmetries, such as: contemporaneous impact, distributed lag effect, cumulated impact, reaction time, equilibrium and momentum equilibrium adjustment path, regime effect, regime equilibrium adjustment path. Each empirical study is then critically discussed in the light of this new classification of asymmetries. Third, this paper evaluates the relative merits of the most popular econometric models for price asymmetries, namely autoregressive distributed lags, partial adjustments, error correction models, regime switching and vector autoregressive models. Finally, we use the meta‐regression analysis to investigate whether the results of asymmetry tests are not model‐invariant and find which additional factors systematically influence the rejection of the null hypothesis of symmetric price adjustment. The main results of our survey can be summarized as follows: (i) each econometric model is specialized to capture a subset of asymmetries; (ii) each asymmetry is better investigated by a subset of econometric models; (iii) the general significance of the F test for asymmetric price transmission depends mainly on characteristics of the data, dynamic specification of the econometric model, and market characteristics. Overall, our empirical findings confirm that asymmetry, in all its forms, is very likely to occur in a wide range of markets and econometric models.     

Investigating properties of commodity price responses to real and nominal shocks

This paper studies dynamic adjustments of 49 world commodity prices in response to innovations in the nominal exchange rate and the world real GDP. After we estimate the dynamic elasticity of the prices with respect to these shocks, we obtain the kernel density of our estimates to establish stylized facts on the adjustment process of the commodity price toward a new equilibrium path. Our empirical findings imply, on average, that the law of one price holds in the long-run, whereas the substantial degree of short-run price rigidity was observed in response to the nominal exchange rate shock. The real GDP shock tends to generate substantial price fluctuations in the short-run because adjustments of the supply can be limited, but have much weaker effects in the long-run as the supply eventually counterbalances the increase in the demand. Overall, we report persistent long-lasting effects of the nominal exchange rate shock on commodity prices relative to those of the real GDP shock.     

A continuity property for local price adjustment mechanisms

This paper makes a case that a (local) continuity property is a reasonable one for any local price adjustment mechanism. This property means that if the starting points (i.e., initial prices) of the adjustment process are ‘close' to one another, and if the characteristics of the economies are ‘close' to one another, then, given any price adjustment mechanism, agents should compute equilibria that are ‘close' to one another. Under preferences which satisfy a ‘surjectivity hypothesis', it is shown that the tâtonnement process satisfies this continuity property on a nice subset of the space of all economies. A characterization of these economies for which the tâtonnement process is locally stable is given. Chart logic is a useful way to think about the path dependent property of implied volatility and about the relationship between implied volatility and historical volatility.     

Sluggish quantity adjustment in a non-clearing market—a disequilibrium econometric application to the loan market

The paper argues that the estimated speed of price adjustment in a disequilibrium econometric model is likely to be biased if allowance is not made for quantity adjustment inertia on both sides of the market. Furthermore, if the model estimated is static rather than dynamic then, in certain circumstances, an excess demand regime may be mistaken for one of excess supply and vice-versa. In an empirical application to the loan market for the clearing banks in Ireland we can claim to have obtained some support for this belief.     

Price Discrimination in Input–Output

Modern economies are characterized by a great variety of pricing rules. Therefore, the commodities' prices and the primay factors' prices are discriminated in reality. However, in practical input–output tables, as well as in theoy, the prices are uniform and relative. In this work, an input–output model is described with absolute and different prices for final uses commodities and production's primay factors (wages, profits, etc.). In this case, the economic relationships are based on the commodities' demand curves for all the categories of final uses, and the factors' supply curves for all production's branches. In this way, we can establish the linkage and the feedback between factors' prices and quantities, and final uses commodities' prices and quantities. This is obtained by a novel interpretation of input–output, which approximates reality better.     

房价空间关联的动力机制——基于空间Durbin模型的实证研究

城市房价的一个重要特征就是其空间关联性。分析了房价空间关联的四种动力机制,基于一个消费者均衡模型并利用268个城市的房价数据,应用空间Durbin模型实证检验了城市房价的空间关联性。研究表明,我国城市房价存在显著的空间关联性和明显的地区差异,相对于东中部城市,西部城市间房地产市场至少在现阶段还缺乏城市问的关联机制。     

Time-varying (S, s) band models: Properties and interpretation

A recent strand of empirical work uses (S, s) models with time-varying stochastic bands to describe infrequent adjustments of prices and other variables. The present paper examines some properties of this model, which encompasses most micro-founded adjustment rules rationalizing infrequent changes. We illustrate that this model is flexible enough to fit data characterized by infrequent adjustment and variable adjustment size. We show that, to the extent that there is variability in the size of adjustments (e.g. if both small and large price changes are observed), (i) a large band parameter is needed to fit the data and (ii) the average band of inaction underlying the model may differ strikingly from the typical observed size of adjustment. The paper thus provides a rationalization for a recurrent empirical result: very large estimated values for the parameters measuring the band of inaction.