Posted Content•
Using financial markets information to identify oil supply shocks in a restricted VAR
TL;DR: In this article, a methodology for identifying oil supply shocks in a restricted VAR system for a small open economy is introduced, which is applied to Finland and Sweden in illustrative examples in a simple 5-variable model.
Abstract: This paper introduces a methodology for identifying oil supply shocks in a restricted VAR system for a small open economy. Financial market information is used to construct an identification scheme that forces the response of the restricted VAR model to an oil shock to be the same as that implied by futures markets. Impulse responses are then calculated by using a bootstrapping procedure for partial identification. The methodology is applied to Finland and Sweden in illustrative examples in a simple 5-variable model. While oil supply shocks have an inflationary effect on domestic inflation in these countries during the past decade or so, the effect on domestic GDP is more ambiguous. Keywords: oil futures, partial identification, macroeconomic shocks JEL classification numbers: C01, E32, E44
Citations
More filters
TL;DR: In this paper, the interaction of private and public funding of innovative projects in the presence of adverse-selection based financing constraints is studied, and it is shown that under certain conditions, public R&D subsidies can reduce the financing constraints of technology-based entrepreneurial firms.
Abstract: We study the interaction of private and public funding of innovative projects in the presence of adverse-selection based financing constraints. Government programs allocating direct subsidies are based on ex ante screening of the subsidy applications. This selection scheme may yield valuable information to market-based financiers. We find that under certain conditions, public R&D subsidies can reduce the financing constraints of technology-based entrepreneurial firms. First, the subsidy itself reduces the capital costs related to the innovation projects by reducing the amount of market-based capital required. Second, the observation that an entrepreneur has received a subsidy for an innovation project provides an informative signal to the market-based financiers. We also find that public screening works more efficiently if it is accompanied with subsidy allocation.
210 citations
TL;DR: In this article, the authors revisited the issue from the vantage point of close to two decades of additional experience by examining a sample of foreign IPOs from both financially integrated and segmented markets in U.S. markets.
Abstract: While the signaling hypothesis has played a prominent role as the economic rationale associated with the initial public offering (IPO) underpricing puzzle (Welch (1989)), the empirical evidence on it has been mixed at best (Jegadeesh, Weinstein, and Welch (1993), Michaely and Shaw (1994)). This paper revisits the issue from the vantage point of close to two decades of additional experience by examining a sample of foreign IPOs—firms from both financially integrated and segmented markets—in U.S. markets. The evidence indicates that signaling does matter in determining IPO underpricing, especially for firms domiciled in countries with segmented markets, which as a result face higher information asymmetry and lack access to external capital markets. We find a significant positive and robust relationship between the degree of IPO underpricing and segmented-market firms’ seasoned equity offering (SEO) activities. For firms from integrated markets, in contrast, the analyst-coverage purchase hypothesis appears to matter more in explaining IPO underpricing, and the aftermarket price appreciation explains these firms’ SEO activities. The evidence, therefore, clearly supports the notion that some firms are willing to leave money on the table voluntarily to get a more favorable price at seasoned offerings when they are substantially wealth constrained, a prediction embedded in the signaling hypothesis.
94 citations
TL;DR: In this article, the authors investigate the impact of bank competition on the use of collateral in loan contracts and show that the presence of collateral is more likely when bank competition is low.
Abstract: We investigate the impact of bank competition on the use of collateral in loan contracts. We analyze asymmetric information about the borrowers’ type in a Salop model in which banks choose between screening the borrower and asking for collateral. We show that the presence of collateral is more likely when bank competition is low. We then test this prediction empirically on a sample of bank loans from 70 countries. We perform logit regressions of the presence of collateral on bank competition, measured by the Lerner index. Our empirical tests corroborate the theoretical predictions that bank competition reduces the presence of collateral. These findings survive several robustness checks.
80 citations
TL;DR: In this paper, the authors deal with optimal payment systems and present a short review of calculation methods and empirical results for a sample of countries, including Finland, which is to an extent one of the front-runners in payment technology and institutional design in payment systems.
Abstract: This paper deals with optimal payment systems. The issue boils down to how large are the costs of different payment media, which can be interpreted as a question of the efficiency of the means of payment. However, there are other qualifications related to the choice of payment media. Here, at least three issues can be distinguished. First is the question of optimal payment medium for each individual payment (size, location, EFTPOS etc.). This choice is not independent of the individual characteristics of the payer and payee. Secondly, there is the question of cost effectiveness of payments for different institutions and sectors. The final issue concerns the social optimum for each payment medium. These issues have been particularly controversial in the case of cash, which is still the dominant payment medium in most euro countries. Part of the controversy arises from the fact that the costs and benefits of different payment media affect different market participants in quite different ways, so that a possible social optimum might not correspond eg to the optima for different firms. The paper contains a short review of calculation methods and empirical results for a sample of countries. It also provides new evidence from Finland, which is to an extent one of the front-runners in payment technology and institutional design in payment systems. This shows up in relatively low overall costs of payments. Our estimate of total costs of payment media is 0.3 per cent of GDP, which is very low by international standards.
42 citations
TL;DR: In this paper, the authors tackle the controversy over whether investment-cash flow sensitivity is a good indicator of financing constraints and cross-validate their analysis with both balance sheet and qualitative data on self-declared credit rationing and financing constraints.
Abstract: The controversy over whether investment-cash flow sensitivity is a good indicator of financing constraints is still unresolved. We tackle it from several different angles and cross-validate our analysis with both balance sheet and qualitative data on self-declared credit rationing and financing constraints. Our qualitative information shows that (self-declared) credit rationing is (weakly) related to both traditional a priori factors - such as firm size, age and location - and lenders' rational decisions based on their credit risk models. We use our qualitative information on firms that were denied credit to provide evidence relevant to the investment-cash flow sensitivity debate. Our results show that self-declared credit rationing significantly discriminates between firms that do and do not have such sensitivity, whereas a priori criteria do not. The same result does not apply when we consider the wider group of financially constrained firms (which do not seem to have a higher investment-cash flow sensitivity), which supports the more recent empirical evidence in this direction.
36 citations
References
More filters
Book•
21 Nov 1994
TL;DR: In this article, the authors present an alternative solution method for Deterministic Processes by iteratively solving homogeneous difference equation and finding particular solutions for deterministic processes, and conclude that the proposed solution is the best solution.
Abstract: PREFACE. ABOUT THE AUTHOR. Chapter DIFFERENCE EQUATIONS . 1 Time-Series Models. 2 Difference Equations and Their Solutions. 3 Solution by Iteration. 4 An Alternative Solution Methodology. 5 The Cobweb Model. 6 Solving Homogeneous Difference Equations. 7 Finding Particular Solutions for Deterministic Processes. 8 The Method of Undetermined Coefficients. 9 Lag Operators. Summary and Conclusions. Questions and Exercises. Endnotes. Appendix 1 Imaginary Roots and de Moivre's Theorem. Appendix 2 Characteristic Roots in Higher-Order Equations. Chapter 2 STATIONARY TIME-SERIES MODELS . 1 Stochastic Difference Equation Models. 2 ARMA Models. 3 Stationarity. 4 Stationarity Restrictions for an ARMA(p, q) Model. 5 The Autocorrelation Function. 6 The Partial Autocorrelation Function. 7 Sample Autocorrelations of Stationary Series. 8 Box-Jenkins Model Selection. 9 Properties of Forecasts. 10 A Model of the Interest Rate Spread. 11 Seasonality. 12 Parameter Instability and Structural Change. Summary and Conclusions. Questions and Exercises. Endnotes. Appendix 1 Estimation of an MA(1) Process. Appendix 2 Model Selection Criteria. Chapter 3 MODELING VOLATILITY . 1 Economic Time Series The Stylized Facts. 2 ARCH Processes. 3 ARCH and GARCH Estimates of Inflation. 4 Two Examples of GARCH Models. 5 A GARCH Model of Risk. 6 The ARCH-M Model. 7 Additional Properties of GARCH Processes. 8 Maximum Likelihood Estimation of GARCH Models. 9 Other Models of Conditional Variance. 10 Estimating the NYSE International 100 Index. 11 Multivariate GARCH. Summary and Conclusions. Questions and Exercises. Endnotes. Appendix 1 Multivariate GARCH Models. Chapter 4 MODELS WITH TREND . 1 Deterministic and Stochastic Trends. 2 Removing the Trend. 3 Unit Roots and Regression Residuals. 4 The Monte Carlo Method. 5 Dickey-Fuller Tests. 6 Examples of the ADF Test. 7 Extensions of the Dickey-Fuller Test. 8 Structural Change. 9 Power and the Deterministic Regressors. 10 Tests with More Power. 11 Panel Unit Root Tests. 12 Trends and Univariate Decompositions. Summary and Conclusions. Questions and Exercises. Endnotes. Appendix 1 The Bootstrap. Chapter 5 MULTIEQUATION TIME-SERIES MODELS . 1 Intervention Analysis. 2 Transfer Function Models. 3 Estimating a Transfer Function. 4 Limits to Structural Multivariate Estimation. 5 Introduction to VAR Analysis. 6 Estimation and Identification. 7 The Impulse Response Function. 8 Testing Hypothesis. 9 Example of a Simple VAR Terrorism and Tourism in Spain. 10 Structural VARs. 11 Examples of Structural Decompositions. 12 The Blanchard and Quah Decomposition. 13 Decomposing Real and Nominal Exchange Rate Movements An Example. Summary and Conclusions. Questions and Exercises. Endnotes. Chapter 6 COINTEGRATION AND ERROR-CORRECTION MODELS . 1 Linear Combinations of Integrated Variables. 2 Cointegration and Common Trends. 3 Cointegration and Error Correction. 4 Testing for Cointegration The Engle-Granger Methodology. 5 Illustrating the Engle-Granger Methodology. 6 Cointegration and Purchasing-Power Parity. 7 Characteristic Roots, Rank, and Cointegration. 8 Hypothesis Testing. 9 Illustrating the Johansen Methodology. 10 Error-Correction and ADL Tests. 11 Comparing the Three Methods. Summary and Conclusions. Questions and Exercises. Endnotes. Appendix 1 Characteristic Roots Stability and Rank. Appendix 2 Inference on a Cointegrating Vector. Chapter 7 NONLINEAR TIME-SERIES MODELS . 1 Linear Versus Nonlinear Adjustment. 2 Simple Extensions of the ARMA Model. 3 Regime Switching Models. 4 Testing For Nonlinearity. 5 Estimates of Regime Switching Models. 6 Generalized Impulse Responses and Forecasting. 7 Unit Roots and Nonlinearity. Summary and Conclusions. Questions and Exercises. Endnotes. STATISTICAL TABLES. A. Empirical Cumulative Distributions of the tau. B. Empirical Distribution of PHI . C. Critical Values for the Engle-Granger Cointegration Test. D. Residual Based Cointegration Test with I (1) and I (2) Variables. E. Empirical Distributions of the lambda max and lambda trace Statistics. F. Critical Values for beta 1 = 0 in the Error-correction Model. G. Critical Values for Threshold Unit Roots. REFERENCES. SUBJECT INDEX.
6,373 citations
04 Oct 2007
TL;DR: This reference work and graduate level textbook considers a wide range of models and methods for analyzing and forecasting multiple time series, which include vector autoregressive, cointegrated, vector Autoregressive moving average, multivariate ARCH and periodic processes as well as dynamic simultaneous equations and state space models.
Abstract: This reference work and graduate level textbook considers a wide range of models and methods for analyzing and forecasting multiple time series. The models covered include vector autoregressive, cointegrated, vector autoregressive moving average, multivariate ARCH and periodic processes as well as dynamic simultaneous equations and state space models. Least squares, maximum likelihood, and Bayesian methods are considered for estimating these models. Different procedures for model selection and model specification are treated and a wide range of tests and criteria for model checking are introduced. Causality analysis, impulse response analysis and innovation accounting are presented as tools for structural analysis. The book is accessible to graduate students in business and economics. In addition, multiple time series courses in other fields such as statistics and engineering may be based on it. Applied researchers involved in analyzing multiple time series may benefit from the book as it provides the background and tools for their tasks. It bridges the gap to the difficult technical literature on the topic.
5,244 citations
TL;DR: The authors found that all but one of the U.S. recessions since World War II have been preceded, typically with a lag of around three-fourths of a year, by a dramatic increase in the price of crude petroleum.
Abstract: All but one of the U.S. recessions since World War II have been preceded, typically with a lag of around three-fourths of a year, by a dramatic increase in the price of crude petroleum. This does not mean that oil shocks caused these recessions. Evidence is presented, however, that even over the period 1948-72 this correlation is statistically significant and nonspurious, supporting the proposition that oil shocks were a contributing factor in at least some of the U.S. recessions prior to 1972. By extension, energy price increases may account for much of post-OPEC macroeconomic performance.
3,391 citations
Posted Content•
TL;DR: In this paper, a structural decomposition of the real price of crude oil in four components is proposed: oil supply shocks driven by political events in OPEC countries; other oil supply shock; aggregate shocks to the demand for industrial commodities; and demand shocks that are specific to the crude oil market.
Abstract: Using a newly developed measure of global real economic activity, a structural decomposition of the real price of crude oil in four components is proposed: oil supply shocks driven by political events in OPEC countries; other oil supply shocks; aggregate shocks to the demand for industrial commodities; and demand shocks that are specific to the crude oil market. The latter shock is designed to capture shifts in the price of oil driven by higher precautionary demand associated with concerns about the availability of future oil supplies. The paper quantifies the magnitude and timing of these shocks, their dynamic effects on the real price of oil and their relative importance in determining the real price of oil during 1975-2005. The analysis also sheds light on the origins of the major oil price shocks since 1979. Distinguishing between the sources of higher oil prices is shown to be crucial for assessing the effect of higher oil prices on U.S. real GDP and CPI inflation. It is shown that policies aimed at dealing with higher oil prices must take careful account of the origins of higher oil prices. The paper also quantifies the extent to which the macroeconomic performance of the U.S. since the mid-1970s has been determined by the external economic shocks driving the real price of oil as opposed to domestic economic factors and policies.
2,951 citations
TL;DR: In this paper, the authors proposed a rank test based on matrix perturbation theory, which overcomes deficiencies of existing rank statistics, such as: a Kronecker covariance matrix for the canonical correlation rank statistic of Anderson [Annals of Mathematical Statistics (1951), 22, 327-351] sensitivity to the ordering of the variables for the LDU rank statistics of Cragg and Donald [1996, 91, 1301-1309] and Gill and Lewbel [Journal of the American Statistical Association (1992), 87, 766-776] a limiting
2,125 citations