Augmented Dickey-Fuller Statistic Research Articles

Sectorial Allocation of Banks’ Assets and Profitability of Commercial Banking Sector in Nigeria

This study examines sectorial allocation of banks’ assets and profitability of commercial banking sector in Nigeria. The study made use of return on assets (ROA) as proxy for dependent variable measuring profitability of commercial banks in Nigeria while banks assets allocations to Petroleum Sector, Breweries Sector, Conglomerates Sector, Agricultural Sector, Construction Sector and Fast Moving Consumer Goods Sector, was used in the study as independent variables. All data were obtained from Central Bank of Nigeria statistical bulletin and which span across 2008 to 2022. Data stationarity was ensured using the Augmented Dickey Fuller statistics, while the error correction model was applied to as the statistical tool for acceptance of hypothesis. The study also upholds the bank-based systems and that of the commercial bank theory. Sectorial allocation to the Petroleum Sector (PETR), Breweries Sector (BREW), Conglomerates Sector (CONG), Agricultural Sector (AGRIC), Construction Sector (CONS), Fast Moving Consumer Goods Sector (FMCG) is significant and positive and contributed positively to return on assets (ROA), government should ensure the proper financing and monitoring of these sectors. No causality between FCMG and PETR. PETR, BREW, CONG, AGRIC, CONS, FCMG granger cause ROA. There is a bi-directional relationship between PETR and ROA; BREW and ROA; CONG and ROA; AGRIC and ROA; CONS and ROA; and FMCG and ROA. The current risky business environment is affecting banks’ ability to lend to the Petroleum Sector (PETR), Breweries Sector (BREW), Conglomerates Sector (CONG), Agricultural Sector (AGRIC), Construction Sector (CONS), Fast Moving Consumer Goods Sector (FMCG). Commercial bank assets allocated to Fast Moving Consumer Goods (FMCG) and allocation of banks’ assets to conglomerate sector (CONG) exhibited a negative coefficients, thus suggesting reject the alternate hypothesis, and accept the null hypothesis which states that t here is no signi

DETERMINANTS OF DOMESTIC SUPPLY OF COCOA IN NIGERIA (1980-2019)

This study examined the factors influencing the domestic supply of cocoa in Nigeria. Time series data covering the period between 1980 and 2017 were used in the study. Data on the domestic supply of cocoa, domestic and international prices of cocoa, volume of cocoa exports, exchange rate, inflation rate, and agricultural gross domestic product (agGDP) were obtained from reputable secondary sources such as the Central Bank of Nigeria (CBN), the National Bureau of Statistics (NBS) and Food and Agriculture Organization Statistical databases (FAOSTAT). Data were analysed using Augmented Dickey-Fuller statistics, Johansen’s co-integration test, descriptive statistics, trend model, and error correction models at a level of significance α = 0.05. There was a high fluctuation in the trend of the domestic supply of cocoa over the study period. The average annual percentage change in the domestic supply of cocoa was 8.092 percent. The coefficients of variation revealed a high degree of instability in the domestic supply of cocoa, ranging from a low of 11.510 percent in the 2010-2017 sub-period to the highest of 122.340 percent in the 2000-2009 sub-period. The producer price of cocoa steadily decreases over the study period. The average producer price of cocoa over the study period was ₦1935.80 per tonne. The average annual percentage change in producer price of cocoa over the study period is 4.900 percent. The coefficient of variation ranged from a low 25.130 percent in the 2000-2009 sub-period to the highest 130.370 percent in the 1990-1999 sub-period, showing high instability in the producer price of cocoa over the study period. The contribution of cocoa to agricultural exports is unstable over the study period. The average percentage contribution of cocoa to agricultural export over the study period was 84.300 percent. The results of error correction analysis revealed that the domestic supply of cocoa is negatively influenced by interest rate, inflation rate, and producer price of cocoa. Thus, it can be concluded that cocoa is a significant agricultural export commodity, but there is a need to pay significant policy attention to these macroeconomic variables for an increased domestic supply of cocoa.

NONSTATIONARY LINEAR PROCESSES WITH INFINITE VARIANCE GARCH ERRORS

Recently, Cavaliere, Georgiev, and Taylor (2018, Econometric Theory 34, 302–348) (CGT) considered the augmented Dickey–Fuller (ADF) test for a unit-root model with linear noise driven by i.i.d. infinite variance innovations and showed that ordinary least squares (OLS)-based ADF statistics have the same distribution as in Chan and Tran (1989, Econometric Theory 5, 354–362) for i.i.d. infinite variance noise. They also proposed an interesting question to extend their results to the case with infinite variance GARCH innovations as considered in Zhang, Sin, and Ling (2015, Stochastic Processes and their Applications 125, 482–512). This paper addresses this question. In particular, the limit distributions of the ADF for random walk models with short-memory linear noise driven by infinite variance GARCH innovations are studied. We show that when the tail index $\alpha <2$ , the limit distributions are completely different from that of CGT and the estimator of the parameters of the lag terms used in the ADF regression is not consistent. This paper provides a broad treatment of unit-root models with linear GARCH noises, which encompasses the commonly entertained unit-root IGARCH model as a special case.

Sectorial Allocation of Bank Credits and Economic Development in Nigeria

This study examines sectorial allocation of bank credits and economic development in Nigeria. The study made use of human development index as proxy for dependent variable measuring economic development while bank credits to public sector, manufacturing, agricultural, mining general commerce sector, real estate and construction, was used in the study as independent variables. All data were obtained from Central Bank of Nigeria statistical bulletin and index-mudi which span across 1985 to 2019. Data stationarity was ensured using the Augmented Dickey Fuller statistics, while the error correction model was applied to as the statistical tool for acceptance of hypothesis. The results of the analysis showed that bank credits to manufacturing, mining and general commerce sector contributed negatively to human development index while bank credit to public sector, real estate and agricultural sector contributed positively to human development index. The study also upholds the bank-based systems and that of the commercial bank theory. The current risky business environment is affecting banks’ ability to lend to the manufacturing, mining and general commerce sector which ought to drive development. This study recommends that monetary authorities should control key macro-economic factors; this will enable the banking sector to create more credit for the economy. Thereby enhancing investment and employment opportunities which on the other hand will boast economic development in the country.

Effect of Globalization on Nigerian Financial Sector

The study examined the effect of globalization on the Nigerian financial sector and to ascertain the contribution of globalization on the Nigerian stock exchange and commercial banks. Assets of the Nigerian stock exchange and commercial banks were used as performance indicators. The data used are Nigerian yearly data from 1983 to 2014; the data were analyzed using descriptive statistics, ordinary least square statistical technique, Johannes’s co-integration and error correction mechanism. We used Augmented Dickey-fuller statistics test for stationary. We proxy globalization with degree of openness measured by total trade divided by gross domestic product, foreign direct investment flows, Real Gross Domestic Product, external debt flows, nominal exchange rate and gross capital formation. Two null hypotheses were formulated and were tested. They were rejected based on overall significant of models using F statistics at 5 percent level of significance. The result of our estimate based on overall significant of models using F statistics at 5 percent level of significance shows that Nigerian financial sector as a whole has benefited from globalization. Some of the globalization proxy variables take out a priori signs while some did not. However, the foreign direct investment flows and Real Gross Domestic Product affected the performance of the Nigeria Stock Exchange and commercial banks positively while degree of openness, external debt flows, nominal exchange rate and gross capital formation affected the Nigeria stock exchange and Commercial Banks negatively. This shows that Nigerian foreign trade is low. External debt flow has a negative effect on the Nigerian stock Exchange and positive on commercial banks. Nigeria should discourage external loans. Gross capital formation and external debt flows affected the Nigeria stock exchange negatively. We therefore recommend that the recent re-capitalization and debt recovery exercise and monitoring macroeconomic stability be encouraged to gain confidence by investors in the financial sector.

Effect of Globalization on Nigerian Financial Sector

The study examined the effect of globalization on the Nigerian financial sector and to ascertain the contribution of globalization on the Nigerian stock exchange and commercial banks. Assets of the Nigerian stock exchange and commercial banks were used as performance indicators. The data used are Nigerian yearly data from 1983 to 2014; the data were analyzed using descriptive statistics, ordinary least square statistical technique, Johannes’s co-integration and error correction mechanism. We used Augmented Dickey-fuller statistics test for stationary. We proxy globalization with degree of openness measured by total trade divided by gross domestic product, foreign direct investment flows, Real Gross Domestic Product, external debt flows, nominal exchange rate and gross capital formation. Two null hypotheses were formulated and were tested. They were rejected based on overall significant of models using F statistics at 5 percent level of significance. The result of our estimate based on overall significant of models using F statistics at 5 percent level of significance shows that Nigerian financial sector as a whole has benefited from globalization. Some of the globalization proxy variables take out a priori signs while some did not. However, the foreign direct investment flows and Real Gross Domestic Product affected the performance of the Nigeria Stock Exchange and commercial banks positively while degree of openness, external debt flows, nominal exchange rate and gross capital formation affected the Nigeria stock exchange and Commercial Banks negatively. This shows that Nigerian foreign trade is low. External debt flow has a negative effect on the Nigerian stock Exchange and positive on commercial banks. Nigeria should discourage external loans. Gross capital formation and external debt flows affected the Nigeria stock exchange negatively. We therefore recommend that the recent re-capitalization and debt recovery exercise and monitoring macroeconomic stability be encouraged to gain confidence by investors in the financial sector.

Five-Year Antimicrobial Resistance Patterns of Urinary Escherichia coli at an Australian Tertiary Hospital: Time Series Analyses of Prevalence Data.

This study describes the antimicrobial resistance temporal trends and seasonal variation of Escherichia coli (E. coli) urinary tract infections (UTIs) over five years, from 2009 to 2013, and compares prevalence of resistance in hospital- and community-acquired E. coli UTI. A cross sectional study of E. coli UTIs from patients attending a tertiary referral hospital in Canberra, Australia was undertaken. Time series analysis was performed to illustrate resistance trends. Only the first positive E. coli UTI per patient per year was included in the analysis. A total of 15,022 positive cultures from 8724 patients were identified. Results are based on 5333 first E. coli UTIs, from 4732 patients, of which 84.2% were community-acquired. Five-year hospital and community resistance rates were highest for ampicillin (41.9%) and trimethoprim (20.7%). Resistance was lowest for meropenem (0.0%), nitrofurantoin (2.7%), piperacillin-tazobactam (2.9%) and ciprofloxacin (6.5%). Resistance to amoxycillin-clavulanate, cefazolin, gentamicin and piperacillin-tazobactam were significantly higher in hospital- compared to community-acquired UTIs (9.3% versus 6.2%; 15.4% versus 9.7%; 5.2% versus 3.7% and 5.2% versus 2.5%, respectively). Trend analysis showed significant increases in resistance over five years for amoxycillin-clavulanate, trimethoprim, ciprofloxacin, nitrofurantoin, trimethoprim-sulphamethoxazole, cefazolin, ceftriaxone and gentamicin (P<0.05, for all) with seasonal pattern observed for trimethoprim resistance (augmented Dickey-Fuller statistic = 4.136; P = 0.006). An association between ciprofloxacin resistance, cefazolin resistance and ceftriaxone resistance with older age was noted. Given the relatively high resistance rates for ampicillin and trimethoprim, these antimicrobials should be reconsidered for empirical treatment of UTIs in this patient population. Our findings have important implications for UTI treatment based on setting of acquisition.

Financial Development and Economic Growth: A Revised Empirical Study for Ireland

1. Introduction The issue of causal relationship between financial development and economic growth has been an intensive subject of interest for many theoretical and empirical studies (Thalassinos and Kiriazidis, 2003; Thalassinos and Pociovalisteanu, 2007). The main objective of this study is to investigate the causal relationship between economic growth and financial development taking into account the positive effect of industrial production index. Ireland consists one of the most important developed countries of European Union characterized by a high rate of economic growth, a constant monetary and fiscal economic policy and very low inflation and unemployment rates, and a healthy and competitive economy. The negative effects of financial crisis are obvious in an unstable world financial system, which is mainly characterized by an economic instability, while a possible increase of credit risk causes a highly banking uncertainty (Thalassinos et al., 2010). The remainder of the paper proceeds as follows: Initially the data and the specification of the multivariate VAR model are described. For this purpose stationarity test and Johansen cointegration analysis are examined taking into account the estimation of vector error correction model. Finally, Granger causality test is applied in order to find the direction of causality between the examined variables of the estimated model. The empirical results are presented analytically and some discussion issues resulted from this empirical study are developed shortly, while the final conclusions are summarized relatively. 2. Data and Methodology In this study the method of vector autoregressive model (VAR) is adopted to estimate the effects of stock and credit market development on economic growth through the effect of industrial production. The use of this methodology predicts the cumulative effects taking into account the dynamic response among economic growth and the other examined variables Pereira and Hu (2000). In order to test the causal relationships, the following multivariate model is to be estimated [GDP.sub.t] = f([SM.sub.t], [BC.sub.t], [IND.sub.t]) (1) Where: [GDP.sub.t] is the gross domestic product, [SM.sub.t] is the general stock market index, [BC.sub.t] are the domestic bank credits to private sector, [IND.sub.t] is the industrial production index. Relating to the econometric analysis this paper is based on the empirical studies of Chang (2002), Chang and Caudill (2005), Shan (2005), Vazakidis (2006), Vazakidis and Adamopoulos 2009a,b,c). Therefore, this empirical study based on the previous published version on 2010 tries to fill some possible theoretical and empirical gaps estimating a larger data sample taking into account the negative effects of financial crisis the last years. The used data are annual covering the period 1965-2011 for Ireland, regarding 2005 as a base year. All time series data are expressed in their levels and are obtained from International Financial Statistics, (International Monetary Fund, 2012). The selected linear model has better statistical estimations than a logarithmic one. The tested results of the logarithmic model proved to be statistical inferior. Unit root tests: Augmented Dickey-Fuller (ADF) test involves the estimation one of the following equations respectively, Seddighi et al (2000): [[DELTA]X.sub.t] = [[delta]X.sub.t-1] + [p.summation over (j=1)] [[delta].sub.j][[DELTA]X.sub.t-j] + [[epsilon].sub.t] (2) [[DELTA]X.sub.t] = [[alpha].sub.0] + [[delta]X.sub.t-1] + [p.summation over (j=1)] [[delta].sub.j][[DELTA]X.sub.t-j] + [[epsilon].sub.t] (3) [[DELTA]X.sub.t] = [[alpha].sub.0] + [[alpha].sub.1]t + [[delta]X.sub.t-1] + [p.summation over (j=1)] [[delta].sub.j][[DELTA]X.sub.t-j] + [[epsilon].sub.t] (3) If the calculated ADF statistic is higher than McKinnon's critical values, then the null hypothesis ([H. …

THE IMPACT OF PERSISTENT CYCLES ON ZERO FREQUENCY UNIT ROOT TESTS

In this paper we investigate the impact of persistent (nonstationary or near nonstationary) cycles on the asymptotic and finite-sample properties of standard unit root tests. Results are presented for the augmented Dickey–Fuller (ADF) normalized bias andt-ratio-based tests (Dickey and Fuller, 1979,Journal of the American Statistical Association745, 427–431; Said and Dickey, 1984;Biometrika71, 599–607). the variance ratio unit root test of Breitung (2002,Journal of Econometrics108, 343–363), and theMclass of unit-root tests introduced by Stock (1999, in Engle and White (eds.),A Festschrift in Honour of Clive W.J. Granger) and Perron and Ng (1996,Review of Economic Studies63, 435–463). We show that although the ADF statistics remain asymptotically pivotal (provided the test regression is properly augmented) in the presence of persistent cycles, this is not the case for the other statistics considered and show numerically that the size properties of the tests based on these statistics are too unreliable to be used in practice. We also show that thet-ratios associated with lags of the dependent variable of order greater than two in the ADF regression are asymptotically normally distributed. This is an important result as it implies that extant sequential methods (see Hall, 1994,Journal of Business &amp; Economic Statistics17, 461–470; Ng and Perron, 1995,Journal of the American Statistical Association90, 268–281) used to determine the order of augmentation in the ADF regression remain valid in the presence of persistent cycles.

Does Past Information Help Predict Future Price Movements in Emerging Capital Markets? Evidence from the Colombo Securities Exchange

This article examines as to whether past stock prices in the Colombo Securities Exchange (CSE) exhibit predictability of future prices by using various statistical tests for the period from 1985 to 2009 on daily data. The findings of various statistical tests generated mixed results. The results of tests on serial correlation, runs test, variance ratio test and tests on the day-of-the-week effect rejected the weak-form of Efficient Market Hypothesis, whereas Augmented Dickey–Fuller (ADF) test and Phillips Perron (PP) unit root tests as well as the month-of-the-year test failed to reject the presence of random walk. Findings of the ADF and PP test statistics implied that daily changes in stock prices cannot be predicted, so that no investor can earn abnormal profits by exploiting past stock price patterns. This indicates the presence of weak-form efficiency in CSE. However, the results of serial correlation tests, runs test and variance ratio test imply that prices of ASPI do not reflect past prices, indicating that future movements of the stock prices can be predicted by using past price movements. The idea that past price information can only partially predict the future movements of prices/returns indicates that other information is also vital in changing stock prices/returns. The article concludes that the weak-form inefficiency is the normal situation in the CSE.

Impact of Tax Reduction Policy on Banking Sector in Pakistan

This study analyzes the impact of tax policy reforms on the profits of banking sector. The empirical results of unit root and Augmented Dickey Fuller (ADF) test reveal that the data series of tax is positively skewed whereas data series of profitability is negatively skewed. The kurtosis value indicates that all the series are platykurtic. From the value of ADF statistics, it is evident that all the variables are non-stationery at log level and are stationary at their first difference. Granger Causality Test shows that profitability of banking does not granger because tax but tax granger cause profitability of banking which depicts that the change in tax rate affects the profitability of banking industries. The study finds that reduction in corporate income tax rates for banking sector has produced positive impact in shape of increased banking sector profits and assets during the period under review.

Cointegration and Nonstationarity in the Context of Multiresolution Analysis

Cointegration has established itself as a powerful means of projecting out long-term trends from time-series data in the context of econometrics. Recent work by the current authors has further established that cointegration can be applied profitably in the context of structural health monitoring (SHM), where it is desirable to project out the effects of environmental and operational variations from data in order that they do not generate false positives in diagnostic tests. The concept of cointegration is partly built on a clear understanding of the ideas of stationarity and nonstationarity for time-series. Nonstationarity in this context is 'traditionally' established through the use of statistical tests, e.g. the hypothesis test based on the augmented Dickey-Fuller statistic. However, it is important to understand the distinction in this case between 'trend' stationarity and stationarity of the AR models typically fitted as part of the analysis process. The current paper will discuss this distinction in the context of SHM data and will extend the discussion by the introduction of multi-resolution (discrete wavelet) analysis as a means of characterising the time-scales on which nonstationarity manifests itself. The discussion will be based on synthetic data and also on experimental data for the guided-wave SHM of a composite plate.

U.S. softwood lumber demand and supply estimation using cointegration in dynamic equations

Abstract This research estimated dynamic supply and demand equations for the U.S. softwood lumber using two-stage least squares. Long-run and ECM equations were derived from the estimated coefficients. Empirical data included monthly observations from 1990 to late 2006. Stationarity of the residuals was explored using Augmented Dickey–Fuller statistics. Results suggest that demand and supply elasticities in both short and long-run are relatively small compared with past studies. The Canadian softwood lumber supply to the U.S. is more price elastic than the domestic softwood lumber supply. U.S. import tariffs have had limited impact on the amount of softwood lumber imported from Canada. Technological progress and end-of-year seasonal effects on softwood lumber demand and supply were significant over this period.

TESTING FOR UNIT ROOTS IN AUTOREGRESSIONS WITH MULTIPLE LEVEL SHIFTS

The asymptotic distributions of augmented Dickey–Fuller (ADF) unit root tests for autoregressive processes with a unit or near-unit root are discussed in the presence of multiple stochastic level shifts of large size occurring independently in time. The distributions depend on a Brownian motion and a Poisson-type jump process. Due to the latter, tests based on standard critical values experience power losses increasing rapidly with the number and the magnitude of the shifts. A new approach to unit root testing is suggested which requires no knowledge of either the location or the number of level shifts, and which dispenses with the assumption of independent shift occurrence. It is proposed to remove possible shifts from a time series by weighting its increments according to how likely it is, with respect to an ad hoc postulated distribution, a shift to have occurred in each period. If the number of level shifts is bounded in probability, the limiting distributions of the proposed test statistics coincide with those of ADF statistics under standard conditions. A Monte Carlo experiment shows that, despite their generality, the new tests perform well in finite samples.We are grateful to Pentti Saikkonen (the co-editor) and two referees for their helpful and constructive comments on earlier versions of this paper. We also thank Soren Johansen, Helmut Lutkepohl, Anders Rahbek, Robert Taylor, and seminar participants at the European University Institute, the University of Copenhagen, and the URCT Conference held in Faro, Portugal, September 29 to October 1, 2005, for useful comments. Both authors are grateful to the Danish Social Sciences Research Council, project 2114-04-001, for financial support.

A simple panel unit root test in the presence of cross‐section dependence

AbstractA number of panel unit root tests that allow for cross‐section dependence have been proposed in the literature that use orthogonalization type procedures to asymptotically eliminate the cross‐dependence of the series before standard panel unit root tests are applied to the transformed series. In this paper we propose a simple alternative where the standard augmented Dickey–Fuller (ADF) regressions are augmented with the cross‐section averages of lagged levels and first‐differences of the individual series. New asymptotic results are obtained both for the individual cross‐sectionally augmented ADF (CADF) statistics and for their simple averages. It is shown that the individual CADF statistics are asymptotically similar and do not depend on the factor loadings. The limit distribution of the average CADF statistic is shown to exist and its critical values are tabulated. Small sample properties of the proposed test are investigated by Monte Carlo experiments. The proposed test is applied to a panel of 17 OECD real exchange rate series as well as to log real earnings of households in the PSID data. Copyright © 2007 John Wiley &amp; Sons, Ltd.

Does purchasing power parity hold in African less developed countries? Evidence from a panel data unit root test

This study tests for long-run relative purchasing power parity among a sample of 27 African less developed countries. For this purpose, a new test advocated by Im and co-workers is employed which allows one to test for unit roots in heterogeneous panel datasets. This is known as the t-bar test, by which purchasing power parity is confirmed or rejected on the basis of whether or not the average augmented Dickey-Fuller statistic based on demeaned data is significantly different from zero. Using quarterly data covering the period 1974-97, purchasing power parity is generally rejected using individual country unit root tests but support is found using the t-bar test. This suggests that low power problems in testing for purchasing power parity can be overcome using this panel data procedure. The findings also support the view that purchasing power parity is most likely to be found among high inflation less developed countries and that the half-life of a one-off random shock to parity is approximately six quarters. These results are generally confirmed for the 1960-73 period. Copyright 2000 by Oxford University Press.

Intertemporal current account balance and the East Asian currency crises

Under the assumption that the balance of the current account must satisfy the expected intertemporal balance, this paper seeks to establish a precondition for the recent currency crises in East Asian countries. Whenever current policy violates the expected intertemporal balance, it is argued that future policy changes (possibly including the exchange rate regime) are anticipated. Using Trehan and Walsh's [1991] result that nonstationarity of the change of assets is evidence of a violation of the expected intertemporal balance, this paper calculates the augmented Dickey-Fuller statistics of the current account prior to the East Asian currency crises. In each of these crises, there is evidence of a persistent violation of intertemporal balance prior to the crisis. There is also evidence of countries being affected by the plight of their neighbors. Their currencies depreciated even though it was not necessary.

Intertemporal Balance, Sustainability and Efficiency of the Exchange Rate Mechanism

Under the assumption that the balance of payments must satisfy the expected intertemporal balance, this paper seeks to establish a pre-condition for a crisis of the Exchange Rate Mechanism (ERM). Proposing that non-stationarity of the growth rate of assets is evidence of a violation of expected intertemporal balance, we calculate Augmented Dickey-Fuller statistics of the growth rate of foreign exchange reserves prior to the ERM crisis in September, 1992 for member states. In all, but one, of the crisis experiences, there is no evidence of a violation of intertemporal balance prior to the month of the crisis. However, the persistent violation of intertemporal balance by Italy prior to the crisis reflects that the fundamental disequilibrium matters to the viability of the ERM. With no evidence of ef ficient allocation of the foreign reserves within the member states, the ERM is exposed to attack by speculators. (JEL Classification: F31, F33)

The relationship between period and spot rates in international maritime markets

This paper evaluates empirically some very common theories of the freight rate generating process in the time charter markets. After a review of the most common assumptions made of the way time charter rates are set, the hypotheses are identified as follows: (a) the Zannetos Hypothesis, (b), the Lagged Zannetos Hypothesis, (c) the Koyck Lag Hypothesis, (d) the Rational Expectation Hypothesis, and (e) the Conventional Wisdom Hypothesis. These hypotheses are tested using statistical cointegration analysis that includes both an Augmented Dickey–Fuller (ADF), and a Johansen likelihood ratio test. Confronted with the data, hypotheses (a) and (b) are rejected outrightly. In the Koyck Lag case, the ADF statistic seem to confirm the hypothesis. A closer look at the numbers reveals that all of the impact on the time charter rates comes from the lagged dependent variable. Hence, the Koyck Lag Hypothesis is rejected. In the Rational Expectation case, the two tests conflicted. Based on the fact that the Rational Expectation Hypothesis includes the lagged dependent variable and that the Johansen test has been found to be a more robust test than the ADF test, the Rational Expectation Hypothesis is rejected. The fifth hypothesis is a reflection of the general bulk industry perception that the time charter rate is impacted by changes in the comparable spot rate and not much by the spot rate levels. In this case both the ADF and the Johansen test accepted the hypothesis for all markets. Thus, the paper concludes that the conventional market explanation of the time charter freight rate setting process is essentially correct–spot rate changes matter spot rate levels do not.

Testing for a unit root in time series with trend breaks

This paper examines the implications of structural breaks for the unit-root property of some post-World War II macroeconomic time series. Based on sequential methods, trend breaks are found for 8 out of the 17 series considered. Conditional on a single break, the augmented Dickey-Fuller test rejects the no-break unit-root null for 5 series. Further, allowing for multiple breaks as opposed to a single break yields little gain against the null. The evidence against the null is much stronger based on recursive instead of sequential tests and weaker based on Phillips-Perron instead of augmented Dickey-Fuller statistics.