Nonlinear minimization estimators in the presence of cointegrating relations

In this paper, we consider estimation of a long-run and a short-run parameter jointly in the presence of nonlinearities. The theory developed establishes limit behavior of minimization estimators of the long- and short-run parameters jointly. Typically, if the long-run parameter that is present in a cointegrating relationship is estimated, its estimator will be superconsistent. Therefore, we may conjecture that the joint minimization estimation of both parameters jointly will result in the same limit distribution for the short-run parameter as if the long-run parameter was known. However, we show that unless a regularity condition holds, this intuition is false in general. This regularity condition, that clearly holds in the standard linear case, is identical to the condition for validity of a two-step Granger–Engle type procedure. Also, it is shown that if the cointegrated variables are measured in deviation from their averages, the standard asymptotic normality result (that one would obtain if the long-run parameter was known) holds.     

Business,housing, and credit cycles

We use multivariate unobserved components models to estimate trend and cyclical components in gross domestic product (GDP), credit volumes, and house prices for the USA and the five largest European economies. With the exception of Germany, we find large and long cycles in credit and house prices, which are highly correlated with a medium‐term component in GDP cycles. Differences across countries in the length and size of cycles appear to be related to the properties of national housing markets. The precision of pseudo real‐time estimates of credit and house price cycles is roughly comparable to that of GDP cycles.     

The linkage between insurance activity and banking credit: Some evidence from dynamic analysis

This paper investigates the long-run and short-run linkages between insurance activity and banking credit for G-7 countries. To minimize the pretest bias and overcome the structural changes, we adopt the bootstrap Granger causality test applied to full sample and subsamples with a fixed window size. The Johansen cointegration test with GMM-IV estimator finds a long-run positive relation between the series. The full sample results of bootstrap Granger causality test show that there is predictive power from life insurance activity to banking credit only for France and Japan, while the short-run causal relationships between nonlife insurance activity and banking credit are country-specific. However, parameter stability test results suggest that the short-run results in full sample are unreliable. The results of rolling VAR models report that the causal linkages between them are time-varying across various subsamples. These findings offer some useful insights for achieving the co-evolution between insurance and banking credit markets.     

R&D policy in a volatile economy

The literature on R&D-based growth establishes that market equilibrium is inefficient and derives optimal R&D policy. Normative analyses of this type use the assumption of steady state, largely motivated by analytical convenience. This paper questions this steady-state approach by introducing endogenous cycles as long-run equilibria. We show that the government fails to maximize welfare if policy which is optimal in steady state is myopically applied in cyclical equilibria. More specifically, we demonstrate that (i) cycles arise in the (very) standard R&D-based model of Grossman and Helpman [1991. Innovation and Growth in the Global Economy. MIT Press, Cambridge, MA (Chapter 3)] once the model is framed in discrete time, (ii) these cycles are inefficient in the sense that they prevent welfare maximization, (iii) optimal steady-state R&D policy fails to eliminate cycles, and can even create inefficient cycles, (iv) the application of R&D subsidies leads to a trade-off between growth and macroeconomic stability, and (v) optimal R&D policy in a fluctuating economy is state-dependent, which generalizes optimal steady-state R&D policy.     

The Beveridge–Nelson decomposition in retrospect and prospect

Beveridge and Nelson [Beveridge, Stephen, Nelson, Charles R., 1981. A new approach to decomposition of economic time series into permanent and transitory components with particular attention to measurement of the ‘business cycle’. Journal of Monetary Economics 7, 151–174] proposed that the long-run forecast is a measure of trend for time series such as GDP that do not follow a deterministic path in the long run. They showed that if the series is stationary in first differences, then the estimated trend is a random walk with drift that accounts for growth, and the cycle is stationary. In contrast to linear de-trending, the smoother of Hodrick and Prescott (1981) and Hodrick and Prescott [Hodrick, Robert, Prescott, Edward C., 1997. Post-war US business cycles: An empirical investigation. Journal of Money Credit and Banking 29 (1), 1–16] and the unobserved components model of Harvey, [Harvey, A.C., 1985. Trends and cycles in macroeconomic time series. Journal of Business and Economic Statistics 3, 216–227]. Watson [Watson, Mark W., 1986. Univariate detrending methods with stochastic trends Journal of Monetary Economics 18, 49–75] and Clark [Clark, Peter K., 1987. The cyclical component of US economic activity. The Quarterly Journal of Economics 102 (4), 797–814], the BN decomposition attributes most variation in GDP to trend shocks while the cycles are short and brief. Since each is an estimate of the transitory part of GDP that will die out, it seems natural to compare cycle measures by their ability to forecast future growth. The results presented here suggest that cycle measures contain little if any information beyond the short-term momentum captured by BN.     

Stochastic trends,deterministic trends,and business cycle turning points

This study examines the relationship between specifications for long-run output patterns and specifications for business cycle dynamics. In an application to US GDP, it is found that inferences about the nature of the trend in output are not robust to changes in the specification for short-run fluctuations. Similarly, the choice of which model best describes the transitory movements in output depends on the way in which the trend is specified. The empirical analysis makes use of Bayesian methods to compare time series models for US GDP. Inspection of the predictive densities for the individual data points suggests that the information contained in the data is largely limited to the observations associated with business cycle turning points. © 1997 John Wiley & Sons, Ltd.     

Public infrastructure investment,output dynamics,and balanced budget fiscal rules

We study the dynamic macroeconomic effects of public infrastructure investment under a balanced budget fiscal rule, using an overlapping generations model of a small open economy. The government finances public investment by employing distortionary labor taxes. The balanced budget rule implies a negative short-run output multiplier that exceeds (in absolute terms) the positive long-run output multiplier. Larger public capital spillovers sharpen the intertemporal output tradeoff. In contrast to conventional results regarding public investment shocks, we obtain dampened cyclical responses for plausible parameter values. The cyclical dynamics arise from the interaction between the labor tax rate, the tax base, and the intergenerational spillover effects. We show that financing scenarios involving public debt creation can substantially reduce the short-run output contraction and the transitional macroeconomic fluctuations induced by public investment.     

The relationship between carbon dioxide emissions and economic growth: quantile panel-type analysis

This paper samples the data of 138 countries during the 1971–2007 period, and performs an empirical test to validate the relationship between carbon dioxide emissions and economic growth. It first performs panel data analysis and quantile regression analysis to estimate the long-run elasticity relationships, and then analyzes the short-run error correction model to verify the causal relationship between the two. The empirical results indicate the following. (1) The long-run relationship between global carbon dioxide emissions and GDP is stable, with 32.6% of the sampled countries showing cross-coupling of the two (with an elasticity value of greater than 1), 47.1% reporting relative-decoupling (with an elasticity value between 0 and 1), and 20.3% seeing absolute-decoupling (with an elasticity value of smaller than 0). (2) The quantile regression shows that long-run elasticity declines along with the rise of carbon dioxide emission quantiles. In other words, cross-coupling turns into relative-decoupling. (3) The analysis of short-run panel data and quantile regressions mostly support the feedback relationship between carbon dioxide emissions growth and economic growth. This is consistent with the hypothesis developed by Kuznets. (4) According to the results of the quantile regression, the higher the quantiles, the faster and more stable of the short-run error-correction mechanism of the adjustments from short-run disequilibrium to long-run equilibrium. (5) Under the low-quantile carbon dioxide emissions growth and economic growth, the relationship between these two is not stable of the short-run disequilibrium adjustments in the error-correction adjustment process. However, the relationship between these two is steady and feedback in the case of high quantiles. Therefore, the first priority to combat global warming is to focus on the countries with high economic growth and high carbon dioxide emissions growth.     

Shaping buyer–supplier relationships in manufacturing contexts: Design and test of a contingency model

Although the idea that buyer–supplier partnerships can yield considerable benefits to firms is largely diffused among researchers and practitioners, the approach adopted in this paper is that no “one best way” exists in buyer–supplier relationships, but rather a “best way” for each specific exchange context. Hence, this paper proposes a contingency model for shaping and managing buyer–supplier relationships in manufacturing contexts. In order to test the model, an empirical study was performed on a sample of 45 buyer–supplier relationships within the Italian white goods industry. A three-dimensional performance indicator was computed to compare supplier performance achieved within relations matching the model's suggestions with those set differently. The results strongly suggest that suppliers involved in relationships set accordingly to the contingency model are likely to enjoy superior performance.     

On the relationship between the current account and the fiscal balance: The case of Canada

This paper uses an Autoregressive Distributed Lag model to examine the long run and short run relationship between the current account and the fiscal balance, as well as other determinants, using Canadian quarterly data from 1981 to 2018. The results indicate that there is a long-run cointegrating relationship between the current account and the fiscal balance, investment, and private credit. Moreover, the relationship between the current account and the fiscal balance is positive in the long-run, thus providing support for the Keynesian Hypothesis of the fiscal balance driving the current account. Specifically, a one percentage point rise in the fiscal balance to GDP ratio yields a 0.43 percentage point rise in the current account as a percent of GDP. This positive relationship is present in the short-run as well. Finally, the findings from the error correction model yield a speed of adjustment of 0.225, hence 22.5% of the long-run adjustment in the current account occurs next period.     

Forecasting using a periodic transfer function: with an application to the UK price of ferrous scrap

The familiar concept of cointegration enables us to determine whether or not there is a long-run relationship between two integrated time series. However, this may not capture short-run effects such as seasonality. Two series which display different seasonal effects can still be cointegrated. Seasonality may arise independently of the long-run relationship between two time series or, indeed, the long-run relationship may itself be seasonal. The market for recycled ferrous scrap displays these features: the US and UK scrap prices are cointegrated, yet the local markets exhibit different forms of seasonality. The paper addresses the problem of using both cointegrating and seasonal relationships in forecasting time series through the use of periodic transfer function models. We consider the problems of testing for cointegration between series with differing seasonal patterns and develop a periodic transfer function model for the US and UK scrap markets. Forecast comparisons with other time series models suggest that forecasting efficiency may be improved by allowing for periodicity but that such improvement is by no means guaranteed. The correct specification of the periodic component of the model is critical for forecast accuracy.     

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.     

The impact of value added components of GDP and FDI on economic freedom in Europe

This paper investigates the possibility of a long-run relationship between the Economic Freedom Index (EFI), Foreign Direct Investment (FDI) and value added components of GDP in thirty Eastern, Central and Western European countries. The study further examines whether the FDI and sector-specific components of GDP have any significant impact on economic freedom for these countries. We use annual data and employ Pedroni and KAO panel cointegration analyses to assess the long-run relationships. The results indicate that there is a significant long-run relationship between the variables under study. Moreover, the evidence shows that the service and industry value added components positively affect EFI, while the agriculture value added component has a negative effect on EFI. However, contrary to the prior literature, we observe a marginally significant and negative relationship between EFI and FDI in the random effects model.     

The Maastricht inflation criterion: How unpleasant is purgatory?

The Maastricht inflation criterion, designed in the early 1990s to bring “high-inflation” EU countries in line with “low-inflation” countries prior to the introduction of the euro, poses challenges for both new EU member countries and the European Central Bank. While the criterion has positively influenced the public stance toward low inflation, it has biased the choice of the disinflation strategy toward short-run, fiat measures – rather than adopting structural reforms with longer-term benefits – with unpleasant consequences for the efficiency of the eurozone transmission mechanism. The criterion is also unnecessarily tight for new member countries as it mainly reflects cyclical developments.     

A long-run Pure Variance Common Features model for the common volatilities of the Dow Jones

In this paper, a new model to analyze the comovements in the volatilities of a portfolio is proposed. The Pure Variance Common Features model is a factor model for the conditional variances of a portfolio of assets, designed to isolate a small number of variance features that drive all assets’ volatilities. It decomposes the conditional variance into a short-run idiosyncratic component (a low-order ARCH process) and a long-run component (the variance factors). An empirical example provides evidence that models with very few variance features perform well in capturing the long-run common volatilities of the equity components of the Dow Jones.     

Modeling tourism: A fully identified VECM approach

System-based cointegration methods have become popular tools for economic analysis and forecasting. However, the identification of structural relationships is often problematic. Using a theory-directed sequential reduction method suggested by Hall, Henry and Greenslade [Hall, S. G., Henry, S., & Greenslade, J. (2002). On the identification of cointegrated systems in small samples: A modelling strategy with an application to UK wages and prices. Journal of Economic Dynamics and Control, 26, 1517–1537], we estimate a vector error correction model of Hawaii tourism, where both demand and supply-side influences are important. We identify reasonable long-run equilibrium relationships, and Diebold–Mariano tests for forecast accuracy demonstrate satisfactory forecasting performance.     

GRANT EQUIVALENT EXPENDITURE ON INDUSTRIAL SUBSIDIES IN THE POST-WAR UNITED KINGDOM

ABSTRACT The paper constructs a consistent series for UK central government expenditure on industrial subsidies over the post-war period, valuing incentives in grant equivalent terms from the position of a firm undertaking investment appraisal. The analysis includes direct subsidy payments, as well as tax allowances, and provides a disaggregation between those subsidies available on a national, regional and sectoral or firm specific basis. A time-series analysis of the assembled data shows important differences between these components, with regional assistance performing a long-run distributive role, while other elements perform a stabilisation function. The short-run patterns are broadly constant across governments, but the long-run relationships exhibit structural breaks related to both political and economic events.     

Dynamic interactions between Main Street and Wall Street

The paper examines the time-varying relationship between Main Street and Wall Street (proxied by the Dow–Jones industrial index and the Standard & Poor’s 500 index) using cointegration and error-correction techniques. Preliminary results reveal that each pair of series is bounded by a long-run, common stochastic trend and is characterized by significant short-run interactions. The results point to significant inverse effects of lagged GDP changes on the stock price index fluctuations but not vice versa. A suggested interpretation of this finding is that when the economy is doing well then increases in interest rates are expected which would, in turn, adversely affect the stock market.     

Dynamics of fiscal financing in the United States

General equilibrium models that include policy rules for government spending, lump-sum transfers, and distortionary taxation on labor and capital income and on consumption expenditures are fit to US data under rich specifications of fiscal policy rules to obtain several results. First, the best-fitting model allows many fiscal instruments to respond to debt. Second, responses of aggregates to fiscal policy shocks under rich rules vary considerably from responses where only non-distortionary fiscal instruments finance debt. Third, in the short run, all fiscal instruments except labor taxes react strongly to debt, but long-run intertemporal financing comes from all components of the government’s budget constraint. Fourth, debt-financed fiscal shocks trigger long-lasting dynamics; short-run and long-run multipliers can differ markedly.