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In this chapter, using a combination of long-run and sign restrictions to identify aggregate monetary and productivity factors, I find that the monetary factor is responsible for long swings in nominal variables but has little effect on fluctuations in output, real wage, or labor input growth. The productivity factor in addition to increasing output growth and real wage growth in the short and long run, also results in increases in labor input and decreases in prices, but the quantitative effect of the productivity factor on labor input is relatively small. These results are robust to the number of factors included in the model and to alternative priors about the short-run effects of the monetary factor, and to the inclusion of oil prices. Oil prices, in fact, appear to be largely driven by the other aggregate factors.

This chapter advances a panel vector autoregressive/vector error correction model (PVAR/PVECM) framework for purposes of examining the sources and determinants of cross-country variations in macroeconomic performance using large cross-country data sets. Besides capturing the simultaneity of the potential determinants of cross-country variations in macroeconomic performance and carefully separating short- from long-run dynamics, the PVAR/PVECM framework advanced allows to capture a variety of other features typically present in cross-country macroeconomic data, including model heterogeneity and cross-sectional dependence. We use the PVAR/PVECM framework we advance to reexamine the dynamic interrelation between investment in physical capital and output growth. The empirical findings for an unbalanced panel of 90 countries over the time period from at most 1950 to 2000 suggest for most regions of the world surprisingly strong support for a long-run relationship between output and investment in physical capital that is in line with neoclassical growth theory. At the same time, the notion that there would be even a long-run (let alone short-run) causal relation between investment in physical capital and output (or vice versa) is strongly refuted. However, the size of the feedback from output growth to investment growth is estimated to strongly dominate the size of the feedback from investment growth to output growth.

This article investigates the robustness of impulse response estimators to near unit roots and near cointegration in vector autoregressive (VAR) models. We compare estimators based on VAR specifications determined by pretests for unit roots and cointegration as well as unrestricted VAR specifications in levels. Our main finding is that the impulse response estimators obtained from the levels specification tend to be most robust when the magnitude of the roots is not known. The pretest specification works well only when the restrictions imposed by the model are satisfied. Its performance deteriorates even for small deviations from the exact unit root for one or more model variables. We illustrate the practical relevance of our results through simulation examples and an empirical application.

The National commodity exchanges were established in India in the year 2003-2004 to perform the functions of price discovery and price risk management in the economy. The derivatives market can perform these functions properly only if they are efficient and unbiased. So, there is a need to properly evaluate these aspects of the Indian commodity derivatives market. The purpose of this paper is to test the market efficiency and unbiasedness of the Indian soybean futures markets.

The paper uses cointegration and a QARCH-M-ECM-based framework to test the market efficiency and unbiasedness in the soybean futures contract traded in the National Commodity Derivatives Exchange (NCDEX). The cointegration test is used to test the long-run unbiasedness and market efficiency of the contract, while the QARCH-M-ECM model is used to test the short-run market efficiency and unbiasedness of the contract by allowing for a time-varying risk premium. The price data is also tested for presence of structural breaks using a Zivot and Andrews unit root test.

The soybean contract is unbiased in the long run, but there are short-run market inefficiencies and also a presence of a time-varying risk premium. Though the weak form of market efficiency is rejected in the short run, the semi-strong market efficiency is not rejected based on the forecasts.

This is the first paper to consider time-varying risk premium while performing the tests of market efficiency and unbiasedness on Indian commodity markets.

In this paper, the authors aim to investigate the short‐run as well as long‐run market efficiency of Indian commodity futures markets using different asset pricing models. Four agricultural (soybean, corn, castor seed and guar seed) and seven non‐agricultural (gold, silver, aluminium, copper, zinc, crude oil and natural gas) commodities have been tested for market efficiency and unbiasedness.

The long‐run market efficiency and unbiasedness is tested using Johansen cointegration procedure while allowing for constant risk premium. Short‐run price dynamics is investigated with constant and time varying risk premium. Short‐run price dynamics with constant risk premium is modeled with ECM model and short‐run price dynamics with time varying risk premium is modeled using ECM‐GARCH in‐Mean framework.

As far as long‐run efficiency is concerned, the authors find that near month futures prices of most of the commodities are cointegrated with the spot prices. The cointegration relationship is not found for the next to near months futures contracts, where futures trading volume is low. The authors find support for the hypothesis that thinly traded contracts fail to forecast future spot prices and are inefficient. The unbiasedness hypothesis is rejected for most of the commodities. It is also found that for all commodities, some inefficiency exists in the short run. The authors do not find support of time varying risk premium in Indian commodity market context.

In context of Indian commodity futures markets, probably this is the first study which explores the short‐run market efficiency of futures markets in time varying risk premium framework. This paper also links trading activity of Indian commodity futures markets with market efficiency.

A systems approach is applied to UK personal sector holdings of unit trusts, UK company securities, public‐sector long‐term debt and overseas securities. In the long run, asset holdings are determined primarily by hedging considerations but in the short run there is evidence of speculative activity. Asset shares are influenced by relative yields (including capital gains), inflation, and real expenditure. A two‐step estimation procedure is used: a set of cointegration vectors are estimated for asset shares and dynamics are represented by a systems error feedback model. The four equation system is broadly consonant with the data and coefficient estimates are intuitively acceptable.

The implications of trade on developing economies have generated substantial debates with most studies focussed on “openness in the policy”. Hence, the purpose of this study is to focus on “openness in practice”.

This study uses two models and employed the vector error correction model and structural vector autoregression, first, to examine the sectoral effects; second, to investigate the efficacy of neoclassical and new trade theories; and third, to analyse the effect of trade openness shock on Nigerian labour market performance.

The results of the first model showed that trade openness has an adverse effect on employment and wages in both the agriculture and manufacturing sectors. Likewise, the study concludes that the new trade theory explains trade's behaviour on employment and wages in Nigeria. The second model showed that the effect of error shock from trade openness affected wages more than employment.

The study ignores the distributional effects due to unavailability of data.

The study suggested, amongst others, the need for policies mix on the labour market via a coherent set of initiatives in other to increase the competitiveness of Nigeria in the international market.

Most studies focussed on openness in policy through the channels identified in the literature. However, this study investigates these channels in “openness in practice” and investigates trade theories' efficacy on manufacturing and agricultural sectors in Nigeria, which has been neglected in the literature.

The purpose of this paper is to investigate the effects of unanticipated monetary policy innovations on output and price for Ethiopia from 1991:Q1 to 2016:Q1.

Short run and long run identification schemes on structural vector autoregressive model are employed in this study.

The impulse response function results generated show that while a positive shock in interest rate causes a reduction in output and price puzzle, a positive shock to broad money supply has a positive and significant effect on output and price. A positive shock in real effective exchange rate has also an expansionary, though insignificant, effect on impact on both output and price. These results are especially true for the short run identification scheme. As to the results from the variance decomposition, the study shows that the highest variation in output and price is caused by broad money supply shock in the short run.

It adds to the scarce empirical literature on the effects of monetary policy innovations on the Ethiopian economy.

A state space representation of a linearized DSGE model implies a VAR in terms of observable variables. The model is said be non-invertible if there exists no linear rotation of the VAR innovations which can recover the economic shocks. Non-invertibility arises when the observed variables fail to perfectly reveal the state variables of the model. The imperfect observation of the state drives a wedge between the VAR innovations and the deep shocks, potentially invalidating conclusions drawn from structural impulse response analysis in the VAR. The principal contribution of this chapter is to show that non-invertibility should not be thought of as an “either/or” proposition – even when a model has a non-invertibility, the wedge between VAR innovations and economic shocks may be small, and structural VARs may nonetheless perform reliably. As an increasingly popular example, so-called “news shocks” generate foresight about changes in future fundamentals – such as productivity, taxes, or government spending – and lead to an unassailable missing state variable problem and hence non-invertible VAR representations. Simulation evidence from a medium scale DSGE model augmented with news shocks about future productivity reveals that structural VAR methods often perform well in practice, in spite of a known non-invertibility. Impulse responses obtained from VARs closely correspond to the theoretical responses from the model, and the estimated VAR responses are successful in discriminating between alternative, nested specifications of the underlying DSGE model. Since the non-invertibility problem is, at its core, one of missing information, conditioning on more information, for example through factor augmented VARs, is shown to either ameliorate or eliminate invertibility problems altogether.

One of the challenging factors in achieving sustainable growth is the inability of the Nigerian government to diversify the country's revenue base. This study aims to investigate the relationship between cash crop financing and agricultural performance in Nigeria.

Four crops were considered, namely, cotton, cocoa, groundnut and palm oil. The impact of cash crop finance shock on agricultural performance was investigated using the vector error correction model (VECM), while the long-run relationship was examined through the identification of long-run restrictions on the VECM.

The variance decomposition showed that financing shock is more sensitive to cause variation in aggregate employment than aggregate agricultural output in palm oil, while for cocoa, cotton and groundnut showed otherwise. The long-run structural equations exert a positive relationship between cash crop financing and agricultural performance, except for oil palm and cocoa financing that has a negative connection with agrarian employment.

The study is limited to the unavailability of data for agriculture sector capital utilisation, which was not used.

These results show that long-run benefit can be maximised by appropriate funding in cotton and groundnut production to promote sustainable growth.

The study examines the impact of cash crop financing on agricultural performance with the aim to promote sustainable growth in Nigeria using identified VECM.