Regime shifts in stock–flow I(2)–I(1) systems: the case of US fiscal sustainability

In the last two decades, fiscal sustainability has been tested through the use of non‐stationary time series analysis. Two different approximations can be found in the literature: first, a univariate approach that has focused on the stochastic properties of the stock of debt and, second, a multivariate one that has focused on the long‐run properties of the flows of expenditures and revenues, i.e., in the stochastic properties of the deficit. In this paper we unify these approaches considering the stock–flow system that fiscal variables configure. Our approach involves working in an I(2) stochastic processes framework. Given the possibility of the existence of regime shifts in the sustainability of US deficit that the literature has pointed out, we develop a new statistic that can be applied to test several types of I(2) cointegration and multicointegration relationships allowing for regime shifts. To test for these kinds of changing long‐run relationships we propose the use of a residual‐based Dickey–Fuller class of statistic that accounts for one structural break. We show that consistent estimates of the break fraction can be obtained through the minimization of the sum of squared residuals when there is I(2) cointegration. The finite sample performance of the proposed statistic is investigated by Monte Carlo simulations. The econometric methodology is applied to assess whether the US fiscal deficit and debt are sustainable. Copyright © 2010 John Wiley & Sons, Ltd.     

Simulation‐based tests of forward‐looking models under VAR learning dynamics

In this paper we propose a simulation‐based technique to investigate the finite sample performance of likelihood ratio (LR) tests for the nonlinear restrictions that arise when a class of forward‐looking (FL) models typically used in monetary policy analysis is evaluated with vector autoregressive (VAR) models. We consider ‘one‐shot’ tests to evaluate the FL model under the rational expectations hypothesis and sequences of tests obtained under the adaptive learning hypothesis. The analysis is based on a comparison between the unrestricted and restricted VAR likelihoods, and the p‐values associated with the LR test statistics are computed by Monte Carlo simulation. We also address the case where the variables of the FL model can be approximated as non‐stationary cointegrated processes. Application to the ‘hybrid’ New Keynesian Phillips Curve (NKPC) in the euro area shows that (i) the forward‐looking component of inflation dynamics is much larger than the backward‐looking component and (ii) the sequence of restrictions implied by the cointegrated NKPC under learning dynamics is not rejected over the monitoring period 1984–2005. Copyright © 2010 John Wiley & Sons, Ltd.     

Testing the Exogeneity of Argentine Devaluation and Default Risks in Retrospect*

This paper studies the relationship between devaluation and default risks during Argentina's convertibility regime. Before default and devaluation occurred, a harder variant of the currency regime was under discussion. An often‐suggested argument among the supporters of dollarization was that the probability of default could have been reduced by removing fears of devaluation. For this to be true, default risk must be dependent on the devaluation risk. Long‐run relationships and ‘exogeneity’ are examined using a ‘cointegrating vector’ system approach. The results show that only devaluation risk can be modelled on default risk. No empirical evidence is found in favour of dollarization. Moreover, these conclusions are maintained when the information set is expanded to include the Latin American risk and Argentine macroeconomic variables.     

REAL‐TIME DATA AND FISCAL POLICY ANALYSIS: A SURVEY OF THE LITERATURE

This paper surveys the empirical research on fiscal policy analysis based on real‐time data. This literature can be broadly divided into four groups that focus on: (1) the statistical properties of revisions in fiscal data; (2) the political and institutional determinants of projection errors by governments; (3) the reaction of fiscal policies to the business cycle and (4) the use of real‐time fiscal data in structural vector autoregression (VAR) models. It emerges that, first, fiscal revisions are large and initial releases are biased estimates of final values. Secondly, strong fiscal rules and institutions lead to more accurate releases of fiscal data and smaller deviations of fiscal outcomes from government plans. Thirdly, the cyclical stance of fiscal policies is estimated to be more ‘counter‐cyclical’ when real‐time data are used instead of ex post data. Fourthly, real‐time data can be useful for the identification of fiscal shocks. Finally, it is shown that existing real‐time fiscal data sets cover only a limited number of countries and variables. For example, real‐time data for developing countries are generally unavailable. In addition, real‐time data on European countries are often missing, especially with respect to government revenues and expenditures. Therefore, more work is needed in this field.     

Panel data estimates of the production function and product and labor market imperfections

Consistent with two models of imperfect competition in the labor market—the efficient bargaining model and the monopsony model—we provide two extensions of a microeconomic version of Hall's framework for estimating price‐cost margins. We show that both product and labor market imperfections generate a wedge between factor elasticities in the production function and their corresponding shares in revenue, which can be characterized by a ‘joint market imperfections parameter’. Using an unbalanced panel of 10,646 French firms in 38 manufacturing industries over the period 1978–2001, we can classify these industries into six different regimes depending on the type of competition in the product and the labor market. By far the most predominant regime is one of imperfect competition in the product market and efficient bargaining in the labor market (IC‐EB), followed by a regime of imperfect competition in the product market and perfect competition or right‐to‐manage bargaining in the labor market (IC‐PR), and by a regime of perfect competition in the product market and monopsony in the labor market (PC‐MO). For each of these three predominant regimes, we assess within‐regime firm differences in the estimated average price‐cost mark‐up and rent sharing or labor supply elasticity parameters, following the Swamy methodology to determine the degree of true firm dispersion. To assess the plausibility of our findings in the case of the dominant regime (IC‐EB), we also relate our industry and firm‐level estimates of price‐cost mark‐up and extent of rent sharing to industry characteristics and firm‐specific variables respectively. Copyright © 2011 John Wiley & Sons, Ltd.     

MULTIPLE EVENT INCIDENCE AND DURATION ANALYSIS FOR CREDIT DATA INCORPORATING NON‐STOCHASTIC LOAN MATURITY

Applications of duration analysis in economics and finance exclusively employ methods for events of stochastic duration. In application to credit data, previous research incorrectly treats the time to predetermined maturity events as censored stochastic event times. The medical literature has binary parametric ‘cure rate’ models that deal with populations that never experienced the modelled event. We propose and develop a multinomial parametric incidence and duration model, incorporating such populations. In the class of cure rate models, this is the first fully parametric multinomial model and is the first framework to accommodate an event with predetermined duration. The methodology is applied to unsecured personal loan credit data provided by one of Australia's largest financial services organizations. This framework is shown to be more flexible and predictive through a simulation and empirical study that reveals: simulation results of estimated parameters with a large reduction in bias; superior forecasting of duration; explanatory variables can act in different directions upon incidence and duration; and variables exist that are statistically significant in explaining only incidence or duration. Copyright © 2013 John Wiley & Sons, Ltd.     

Safe asset shortages and asset price bubbles

We build a model economy in which a shortage of safe assets can create conditions for intrinsically useless ‘safe’ bubble assets to circulate at a positive price. Our environment features infinitely lived individuals who are not subject to credit constraints but who face uninsurable idiosyncratic production risk. Bubbly equilibria exist when safe assets offer real returns below the growth rate of the economy. Bubble assets circulate at a positive price only if they offer returns which are safe relative to production returns. These ‘safe’ bubbles reduce consumption volatility but exert a contractionary effect on the economy.     

Monetary Policy Indeterminacy and Identification Failures in the U.S.: Results from A Robust Test

We propose a novel identification‐robust test for the null hypothesis that an estimated New Keynesian model has a reduced form consistent with the unique stable solution against the alternative of sunspot‐driven multiple equilibria. Our strategy is designed to handle identification failures as well as the misspecification of the relevant propagation mechanisms. We invert a likelihood ratio test for the cross‐equation restrictions (CER) that the New Keynesian system places on its reduced‐form solution under determinacy. If the CER are not rejected, sunspot‐driven expectations can be ruled out from the model equilibrium and we accept the structural model. Otherwise, we move to a second‐step and invert an Anderson and Rubin‐type test for the orthogonality restrictions (OR) implied by the system of structural Euler equations. The hypothesis of indeterminacy and the structural model are accepted if the OR are not rejected. We investigate the finite‐sample performance of the suggested identification‐robust two‐step testing strategy by some Monte Carlo experiments and then apply it to a New Keynesian AD/AS model estimated with actual US data. In spite of some evidence of weak identification as for the ‘Great Moderation’ period, our results offer formal support to the hypothesis of a switch from indeterminacy to a scenario consistent with uniqueness occurring in the late 1970s. Our identification‐robust full‐information confidence set for the structural parameters computed on the ‘Great Moderation’ regime turns out to be more precise than the intervals previously reported in the literature through ‘limited‐information’ methods. Copyright © 2014 John Wiley & Sons, Ltd.     

Modelling the conditional volatility of commodity index futures as a regime switching process

Commodity index futures offer a versatile tool for gaining different forms of exposure to commodity markets. Volatility is a critical input in many of these applications. This paper examines issues in modelling the conditional variance of futures returns based on the Goldman Sachs Commodity Index (GSCI). Given that commodity markets tend to be ‘choppy’ (Webb, 1987 ), a general econometric model is proposed that allows for abrupt changes or regime shifts in volatility, transition probabilities which vary explicitly with observable fundamentals such as the basis, GARCH dynamics, seasonal variations and conditional leptokurtosis. The model is applied to daily futures returns on the GSCI over 1992–1997. The results show clear evidence of regime shifts in conditional mean and volatility. Once regime shifts are accounted for, GARCH effects are minimal. Consistent with the theory of storage, returns are more likely to switch to the high‐variance state when the basis is negative than when the basis is positive. The regime switching model also performs well in forecasting the daily volatility compared to standard GARCH models without regime switches. The model should be of interest to sophisticated traders who base their trading strategies on short‐term volatility movements, managed commodity funds interested in hedging an underlying diversified portfolio of commodities and investors of options and other derivatives tied to GSCI futures contracts. Copyright © 2001 John Wiley & Sons, Ltd.     

Fiscal and monetary interdependence

Where classical economics integrates the quantity theory of money with the concept of Ricardian equivalence, the tendency of recent macroeconomic presentations is to focus either upon money and inflation or upon taxation and debt. That neglect of classical monetary–fiscal integration is surprising, given an initiative by the International Monetary Fund that set credit, money, and fiscal policy within a single structure. This article places those ‘credit counterparts of broad money’ in the context of the Great Depression and the recent global financial crisis. The upshot is a set of conclusions: that, to counter the prospect of deflation, quantitative easing is a weak policy response; that fiscal deficits are better; and that cuts in taxation are preferable to increased government spending.     

Periodically expanding discounted debt: a threat to fiscal policy sustainability?

This paper models the behaviour of discounted US debt using a Markov‐switching time series model. The significance of modelling fiscal policy within this framework derives from the implications it has for long‐term sustainability. The two‐regime framework used in this paper identifies periods where the present value of US Federal debt is expanding versus periods when it is collapsing. Using an updated data series from Hamilton and Flavin ( 1986 ), a test is conducted to establish if the expanding periods pose a threat to the long‐run sustainability of fiscal policy. For the USA, it is found that they do not. Copyright © 2005 John Wiley & Sons, Ltd.     

Identification and Estimation Issues in Exponential Smooth Transition Autoregressive Models

Exponential smooth transition autoregressive (ESTAR) models are widely used in the international finance literature, particularly for the modelling of real exchange rates. We show that the exponential function is ill‐suited as a regime weighting function because of two undesirable properties. Firstly, it can be well approximated by a quadratic function in the threshold variable whenever the transition function parameter γ, which governs the shape of the function, is ‘small’. This leads to an identification problem with respect to the transition function parameter and the slope vector, as both enter as a product into the conditional mean of the model. Secondly, the exponential regime weighting function can behave like an indicator function (or dummy variable) for very large values of γ. This has the effect of ‘spuriously overfitting’ a small number of observations around the location parameter μ. We show that both of these effects lead to estimation problems in ESTAR models. We illustrate this by means of an empirical replication of a widely cited study, as well as a simulation exercise.     

TESTS OF EQUAL FORECAST ACCURACY FOR OVERLAPPING MODELS

This paper examines the asymptotic and finite‐sample properties of tests of equal forecast accuracy when the models being compared are overlapping in the sense of Vuong (Econometrica 1989; 57 : 307–333). Two models are overlapping when the true model contains just a subset of variables common to the larger sets of variables included in the competing forecasting models. We consider an out‐of‐sample version of the two‐step testing procedure recommended by Vuong but also show that an exact one‐step procedure is sometimes applicable. When the models are overlapping, we provide a simple‐to‐use fixed‐regressor wild bootstrap that can be used to conduct valid inference. Monte Carlo simulations generally support the theoretical results: the two‐step procedure is conservative, while the one‐step procedure can be accurately sized when appropriate. We conclude with an empirical application comparing the predictive content of credit spreads to growth in real stock prices for forecasting US real gross domestic product growth. Copyright © 2013 John Wiley & Sons, Ltd.     

Financial Constraints on German Firms after the Crisis: Evidence from Threshold Panel Estimation

This article studies the existence and magnitude of financial investment constraints in Germany between 2006 and 2012 with a special emphasis on small and medium‐sized firms. The core contention is that the sensitivity of the investment rate to the cash flow rate is a function of a firm's financial position contributing to its access to external finance. The application of a nonlinear panel threshold model reveals that the marginal effect of the cash flow rate on the investment rate is almost twice as strong for ‘high debt’ firms compared to ‘low debt’ firms. This result holds for six out of seven balance sheet threshold variables. For a single specification, the results reveal a non‐monotonic relationship between the cash flow rate and investment rate. Firm size, however, does not explain differences in the cash‐flow‐investment nexus.     

21st‐century models of employee representation: structures,processes and outcomes

The 2004 Workplace Employment Relations Survey allows further exploration of the fate or workplace‐based forms of employee representation charted by earlier surveys. We describe the occurrence and diversity of representational forms, union, non‐union and ‘hybrid’, and the structural characteristics of workplaces where they are found. We go on to analyse a number of structural and processual differences and differences in outcomes. In particular, we try to estimate the effects of different forms for outcomes such as wage dispersion, procedural ‘fairness’ and productivity. The data show that ‘hybrid’ systems of union and non‐union representation are associated with the best outcomes, therefore, notwithstanding the continuing decline in the diffusion of the ‘traditional’ union‐based model of workplace representation, union presence is still a prerequisite for effective representation, while ‘pure’ non‐union forms serve neither employee nor employer interests.     

ESTIMATING FISCAL LIMITS: THE CASE OF GREECE

This paper uses Bayesian methods to estimate a real business cycle model that allows for interactions among fiscal policy instruments, the stochastic ‘fiscal limit’ and sovereign default. Using the particle filter to perform likelihood‐based inference, we estimate the full nonlinear model with post‐EMU data until 2010:Q4. We find that (i) the probability of default on Greek debt was in the range of 5–10% in 2010:Q4 and (ii) the 2011 surge in the Greek real interest rate is within model forecast bands. The results suggest that a nonlinear rational expectations environment can account for the Greek interest rate path. Copyright © 2014 John Wiley & Sons, Ltd.     

A nonlinear investigation of the twin deficits hypothesis over the business cycle: Evidence from Turkey

In this paper, we analyze the twin deficits hypothesis covering the period from 1994 to 2012 in Turkey. In contrast to previous studies on Turkey, the existence of twin deficits is investigated by regime-dependent impulse response functions and forecast error variance decompositions based on a multivariate two-regime threshold VAR (TVAR) model. Our results suggest that the dynamics between the current account and budget account variables are affected by macroeconomic activity: twin deficits are only the case in the upper regime, when the economy operates above its potential level. When the economy is in the lower regime, budget and trade deficits show divergent movements. The results are consistent with Kim and Roubini (2008), indicating that the divergence of fiscal balance and current account might be explained by the cyclical fluctuations of output.     

Too dynamic to fail: empirical support for an autocatalytic model of Minsky’s financial instability hypothesis

Solomon and Golo (Account Econ Law 3(3):167–260, 2013) have recently proposed an autocatalytic (self-reinforcing) feedback model which couples a macroscopic system parameter (the interest rate), a microscopic parameter that measures the distribution of the states of the individual agents (the number of firms in financial difficulty) and a peer-to-peer network effect (contagion across supply chain financing). In this model, each financial agent is characterized by its resilience to the interest rate. Above a certain rate the interest due on the firm’s financial costs exceeds its earnings and the firm becomes susceptible to failure (ponzi). For the interest rate levels under a certain threshold level, the firm loans are smaller then its earnings and the firm becomes ‘hedge.’ In this paper, we fit the historical data (2002–2009) on interest rate data into our model, in order to predict the number of the ponzi firms. We compare the prediction with the data taken from a large panel of Italian firms over a period of 9 years. We then use trade credit linkages to discuss the connection between the ponzi density and the network percolation. We find that the ‘top-down’–‘bottom-up’ positive feedback loop accounts for most of the Minsky crisis accelerator dynamics. The peer-to-peer ponzi companies contagion becomes significant only in the last stage of the crisis when the ponzi density is above a critical value. Moreover the ponzi contagion is limited only to the companies that were not dynamic enough to substitute their distressed clients with new ones. In this respect the data support a view in which the success of the economy depends on substituting the static ‘supply-network’ picture with an interacting dynamic agents one.     

Playing the synthesizer with Canadian data: Adding polls to a structural forecasting model

Election forecasting has become a fixture of election campaigns in a number of democracies. Structural modeling, the major approach to forecasting election results, relies on ‘fundamental’ economic and political variables to predict the incumbent’s vote share usually a few months in advance. Some political scientists contend that adding vote intention polls to these models—i.e., synthesizing ‘fundamental’ variables and polling information—can lead to important accuracy gains. In this paper, we look at the efficiency of different model specifications in predicting the Canadian federal elections from 1953 to 2015. We find that vote intention polls only allow modest accuracy gains late in the campaign. With this backdrop in mind, we then use different model specifications to make ex ante forecasts of the 2019 federal election. Our findings have a number of important implications for the forecasting discipline in Canada as they address the benefits of combining polls and ‘fundamental’ variables to predict election results; the efficiency of varying lag structures; and the issue of translating votes into seats.