The Macroeconomic Effects of Nonzero Trend Inflation

We study the macroeconomic effects of nonzero trend inflation in a simple dynamic stochastic general equilibrium model under three common time-dependent pricing schemes: Calvo, truncated-Calvo, and Taylor. We show that, regardless of the pricing mechanism, trend inflation leads to a reduction in the stochastic means of output, consumption and employment, and an increase in the stochastic mean of inflation beyond its deterministic steady-state level. The variability of most aggregates also increases. These effects are quantitatively much stronger with Calvo pricing.     

An open-economy new Keynesian Phillips curve for the U.K.

We estimate a pricing equation or “new Keynesian Phillips curve” (NKPC) obtained from a structural dynamic model of price setting based on Rotemberg [1982. Sticky prices in the United States. Journal of Political Economy 90(6), 1187-1211] and extended to capture employment adjustment costs and the openness of the United Kingdom. This model nests the baseline Galí and Gertler [1999. Inflation dynamics: a structural econometric analysis. Quarterly Journal of Economics 110, 127-159) and Sbordone [2002. Prices and unit labor costs: a new test of price stickiness. Journal of Monetary Economics 49, 265-292] relationship between inflation and marginal cost in the limiting case of no employment adjustment costs, no impact of relative prices of imported inputs on real marginal cost and a constant equilibrium markup. Our findings indicate that each of our modifications to the baseline NKPC model is important for U.K. data, so that inflation in the U.K. is explained both by changes in employment and by changes in real import prices, in general, and real oil prices, in particular. External competitive pressures also seem to affect U.K. inflation via their impact on the equilibrium price markup of domestic firms.     

Equilibrium asset pricing: with non-Gaussian factors and exponential utilities

We analyse the equilibrium asset pricing implications for an economy with single period return exposures to explicit non-Gaussian systematic factors, that may be both skewed and long-tailed, and Gaussian idiosyncratic components. Investors maximize expected exponential utility and equilibrium factor prices are shown to reflect exponentially tilted prices for non-Gaussian factor risk exposures. It is shown that these prices may be directly estimated from the univariate probability law of the factor exposure, given an estimate of average risk aversion in the economy. In addition, a residual form of the capital asset pricing model continues to hold and prices the idiosyncratic or Gaussian risks. The theory is illustrated on data for the US economy using independent components analysis to identify the factors and the variance gamma model to describe the probability law of the non-Gaussian factors. It is shown that the residual CAPM accounts for no more than 1% of the pricing of risky assets, while the exponentially tilted systematic factor risk exposures account for the bulk of risky asset pricing.     

Two Monetary Models with Alternating Markets

We present a thought‐provoking study of two monetary models: the cash‐in‐advance and the Lagos and Wright ( 2005 ) models. The different approaches to modeling money—reduced form versus explicit role—induce neither fundamental theoretical nor quantitative differences in results. Given conformity of preferences, technologies, and shocks, both models reduce to equilibrium difference equations that coincide unless price distortions are differentially imposed on cash prices, across models. Equal distortions support equally large welfare costs of inflation. Performance differences stem from unequal assumptions about the pricing mechanism that governs cash transactions, not the differential modeling of the monetary exchange process.     

House Prices and Government Spending Shocks

We show that dynamic stochastic general equilibrium (DSGE) models with housing and collateralized borrowing predict a fall in house prices following positive government spending shocks. By contrast, we show that house prices in the United States rise persistently after identified positive government spending shocks. We clarify that the incorrect house price response is due to a general property of DSGE models—approximately constant shadow value of housing—and that modifying preferences and production structure cannot help in obtaining the correct house price response. Properly accounting for the empirical evidence on government spending shocks and house prices using a DSGE model therefore remains a significant challenge.     

In search of the liquidity effect in a modern monetary model

This paper examines the impact of a monetary policy shock in a dynamic stochastic general equilibrium model with sticky prices and financial market frictions. First, we examine the shortcomings of monetary models emphasizing these frictions individually. The model then is specified to limit the response of prices and savings to a current period monetary disturbance. Our results show that this model can account for the following key responses to an expansionary monetary policy shock: a fall in the nominal interest rate; a rise in output, consumption, and investment; and a gradual increase in the price level. Finally, a detailed sensitivity analysis shows the model's results depend on the parameters assigned to critical structural features.     

What Drives the Owner‐Occupied and Rental Housing Markets? Evidence from an Estimated DSGE Model

Most dynamic stochastic general equilibrium (DSGE) models with a housing market do not explicitly include a rental market and assume a tight mapping between house prices and rents over the business cycle. However, rents are much smoother than house prices in the data. We match this feature of the data by adding both an owner‐occupied housing market and a rental market in a standard DSGE model. The intertemporal preference shock accounts for more than half of the variation in house prices and contributes to residential investment fluctuations through the liquidity constraint, and nominal rigidity in rental contracts captures the variation in the price‐rent ratio.     

American option pricing with discrete and continuous time models: An empirical comparison

This paper considers discrete time GARCH and continuous time SV models and uses these for American option pricing. We first of all show that with a particular choice of framework the parameters of the SV models can be estimated using simple maximum likelihood techniques. We then perform a Monte Carlo study to examine their differences in terms of option pricing, and we study the convergence of the discrete time option prices to their implied continuous time values. Finally, a large scale empirical analysis using individual stock options and options on an index is performed comparing the estimated prices from discrete time models to the corresponding continuous time model prices. The results show that, while the overall differences in performance are small, for the in the money put options on individual stocks the continuous time SV models do generally perform better than the discrete time GARCH specifications.     

Random sources correlations and carbon futures pricing

For a long time, the correlation between random sources has never been considered in carbon futures pricing, which virtually exists. We document the presence of high correlation between variations in convenience yields of carbon futures with different maturities, whose essence is correlation between random sources. Correlation of random sources arises from the long coverage of convenience yield of carbon emission spot and the complementarity in expiration between carbon futures with different maturities. Since if random sources are correlated will significantly affect the dynamics of convenience yield and finally affect futures prices, we introduce quantum field method to account for the impact of this correlation on futures prices, and proposes the correlation between random sources extended HJM convenience yield model (CRS-HJM-CYM). Empirical results indicate CRS-HJM-CYM performs better than traditional model owing to the role of correlation, which means the correlation between random sources is a pivotal factor in carbon futures pricing.     

The Phillips curve under state-dependent pricing

We derive a Phillips curve equation from the dynamic stochastic general equilibrium (DSGE) model with state-dependent pricing developed by Dotsey et al. [1999. State-dependent pricing and the general equilibrium dynamics of money and output. Quarterly Journal of Economics 114, 655-690]. This state-dependent Phillips curve encompasses the new Keynesian Phillips curve (NKPC) based on Calvo-type price setting as a special case. We analyze the effect of the state-dependent terms (that is, the variations in the distributions of price vintages) on inflation persistence, and we examine whether the hybrid NKPC (that is, the NKPC extended by a lagged inflation term) can adequately describe inflation dynamics generated in a calibrated state-dependent pricing economy.     

Asset pricing with heterogeneous beliefs

This paper studies the dynamic behavior of security prices in the presence of investors’ heterogeneous beliefs. We provide a tractable continuous-time pure-exchange model and highlight the mechanism through which investors’ differences of opinion enter into security prices. In the determination of equilibrium, we employ a representative investor with stochastic weights and solve for all economic quantities in closed form, including the perceived market prices of risk and interest rate. The basic analysis is generalized to incorporate multiple sources of risk, disagreement about nonfundamentals, and multiple investors. Other applications involving multiple goods and nominal asset pricing within monetary economies are discussed.     

Equilibrium Bitcoin Pricing

We offer a general equilibrium analysis of cryptocurrency pricing. The fundamental value of the cryptocurrency is its stream of net transactional benefits, which depend on its future prices. This implies that, in addition to fundamentals, equilibrium prices reflect sunspots. This in turn implies multiple equilibria and extrinsic volatility, that is, cryptocurrency prices fluctuate even when fundamentals are constant. To match our model to the data, we construct indices measuring the net transactional benefits of Bitcoin. In our calibration, part of the variations in Bitcoin returns reflects changes in net transactional benefits, but a larger share reflects extrinsic volatility.     

Futures Markets and Informational Efficiency: A Laboratory Examination

Through the use of laboratory market methodology, the effect of a futures market on the time path of asset prices is studied and competing models of asset pricing are analyzed. With replication of market conditions, the predictions of a rational expectations equilibrium model are relatively accurate whether or not futures markets are present. However, the presence of futures markets increases the speed with which an efficient equilibrium is achieved. While this more rapid adjustment can increase the variance of spot market prices as they move to equilibrium, this increased variance reflects efficiency gains due to better information.     

The economics of options-implied inflation probability density functions

Recently a market in options based on consumer price index inflation (inflation caps and floors) has emerged in the US. This paper uses quotes on these derivatives to construct probability densities for inflation. We study how these probability density functions respond to news announcements and find that the implied odds of deflation are sensitive to certain macroeconomic news releases. We also estimate empirical pricing kernels using these option prices along with time series models fitted to inflation. The options-implied densities assign considerably more mass to extreme inflation outcomes (either deflation or high inflation) than do their time series counterparts. This yields a U-shaped empirical pricing kernel, with investors having high marginal utility in states of the world characterized by either deflation or high inflation.     

Inflation and output dynamics with state-dependent pricing decisions

This paper studies a state-dependent pricing model in which firms face a fixed cost of changing their pricing plans. A pricing plan specifies an entire sequence of time-varying future prices. Allowing firms to choose a pricing plan rather than a single price generates inflation inertia in the response of the economy to small changes in the growth rate of money. Allowing firms to choose when to change their pricing plan generates a non-linear response of inflation and output to small and large changes in the money growth rate. The non-linear solution method also reveals that the model generates an asymmetric response of output and inflation to monetary expansions and contractions.     

Implications of state-dependent pricing for dynamic macroeconomic models

State-dependent pricing (SDP) models treat the timing of price changes as a profit-maximizing choice, symmetrically with other decisions of firms. Using quantitative general equilibrium models which incorporate a “generalized (S,s) approach,” we investigate the implications of SDP for topics in two major areas of macroeconomic research, the early 1990s SDP literature and more recent work on persistence mechanisms. First, we show that state-dependent pricing leads to unusual macroeconomic dynamics, which occur because of the timing of price adjustments chosen by firms as in the earlier literature. In particular, we display an example in which output responses peak at about a year, while inflation responses peak at about 2 years after the shock. Second, we examine whether the persistence-enhancing effects of two New Keynesian model features, namely specific factor markets and variable elasticity demand curves, depend importantly on whether pricing is state dependent. In an SDP setting, we provide examples in which specific factor markets perversely work to lower persistence, while variable elasticity demand raises it.     

寡头电信企业价格决策微分博弈模型及其分析

在随机需求环境下,电信企业的价格策略表现为一个随时变化的调整轨迹,将寡头电信企业之间的价格竞争博弈刻画为微分博弈模型,并对模型进行了数值模拟和仿真分析,结果表明:在随机需求下,寡头电信企业的价格策略存在唯一的鞍点均衡路径,否则很难实现均衡状态;虽然寡头电信企业的价格处在动态调整中,但市场份额会相对稳定维持在某一均衡状态下。     

Generative Bayesian neural network model for risk-neutral pricing of American index options

Financial models with stochastic volatility or jumps play a critical role as alternative option pricing models for the classical Black–Scholes model, which have the ability to fit different market volatility structures. Recently, machine learning models have elicited considerable attention from researchers because of their improved prediction accuracy in pricing financial derivatives. We propose a generative Bayesian learning model that incorporates a prior reflecting a risk-neutral pricing structure to provide fair prices for the deep ITM and the deep OTM options that are rarely traded. We conduct a comprehensive empirical study to compare classical financial option models with machine learning models in terms of model estimation and prediction using S&P 100 American put options from 2003 to 2012. Results indicate that machine learning models demonstrate better prediction performance than the classical financial option models. Especially, we observe that the generative Bayesian neural network model demonstrates the best overall prediction performance.     

Do Central Banks React to House Prices?

We estimate the Federal Reserve's, the Bank of England's, and the Bank of Japan's responses to house prices. We show that generalized method of moments estimates of a Taylor rule augmented with house prices are biased and dispersed. We then use full‐information methods and estimate the policy rule together with a VAR for the nonpolicy variables. These estimates are also biased. We propose an alternative approach and estimate a dynamic stochastic general equilibrium model embedded with a monetary rule with a direct response to house prices. We find that house prices played a separate role in the reaction functions of these central banks.     

Variance swap dynamics

We compare several parametric and non-parametric approaches for modelling variance swap curves by conducting an in-sample and an out-of-sample analysis using market prices. The forecasted Heston model gives the best overall performance. Moreover, the static Heston model highlights some problems of stochastic volatility models in option pricing of forward starting products.