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We first discuss a phenomenon called data mining. This can involve multiple tests on which variables or correlations are relevant. If used improperly, data mining may associate with scientific misconduct. Next, we discuss one way to arrive at a single final model, involving stepwise methods. We see that various stepwise methods lead to different final models. Next, we see that various configurations in test situations, here illustrated for testing for cointegration, lead to different outcomes. It may be possible to see which configurations make most sense and can be used for empirical analysis. However, we suggest that it is better to keep various models and somehow combine inferences. This is illustrated by an analysis of the losses in airline revenues in the United States owing to 9/11. We see that out of four different models, three estimate a similar loss, while the fourth model suggests only 10 percent of that figure. We argue that it is better to maintain various models, that is, models that stand various diagnostic tests, for inference and for forecasting, and to combine what can be learned from them.
Causal flow analyses combined with time series analyses are used to examine price relationships among fresh broiler retail markets (Northeast, South, Midwest, and West). Results indicate structural changes have occurred in this industry. Reasons for changes in price relationships include the perishable nature of fresh broilers, along with vertical integration and increases in production and concentration in the industry. The four markets are integrated, but the level of integration has decreased over time. With the markets becoming more exogenous, there may be a decrease in society’s welfare. The South market is the most important market for price discovery.
In the wake of the global financial crisis, unemployment rates and openness to trade have been the subject of considerable research, especially in developing countries. This study analyses the impacts of trade policy on unemployment rates in Nigeria. Using time series data from 1970 to 2010, it adopts the vector error correction methodology. In order to explore the impact of a range of variables on the relationship between trade openness and national unemployment rates, these variables, in a system of equations, include measures of trade openness, public recurrent spending on education, foreign price shocks and real gross domestic product or alternatively income per capita. The findings reveal that in the long run, real output and income per capita lead to a decline in unemployment, but trade openness policy is associated with an increase in unemployment. Foreign policy shocks, as proxied by commodity prices, also exert a positive effect on unemployment rates and do not contribute subsequently to restoring the system to equilibrium. However, the initial impact of openness and foreign price shocks captured by short-term dynamics are observed to reduce unemployment.
We use Canadian data over the period of 1991Q1 to 2019Q2 to examine the effect of higher minimum wages on consumption, measured as the real retail trade sales per adult population. Such an examination is rare in the extant literature and it is timely given the increasing debate concerning the stimulus versus inflationary effects arising from wage polices because of COVID-19 global pandemic. We apply the autoregressive distributed lag model to determine the causal relationship between these variables. We find one long-run cointegrating relationship that runs from the real minimum wage to the real retail trade sales. In addition, we find that a 1% increase in the minimum wage is associated with almost a 0.5% increase in real retail trade sales in the long run. While our findings rest on several statistical assumptions, there is strong evidence in support of the position that minimum wage strengthens aggregate consumer spending, and thereby the standard of living, economic growth and stability. This is a position that differs from the conclusions drawn from mainstream academic and policy debates on the economic usefulness and efficacy of minimum wage increases.
Chapter 12 offers some suggestions about how researchers in economics and finance may apply the KU indices and narrative proxies in their own work moving forward. The present value model for the aggregate stock market is used as a case study wherein the SP500 dividend series is adjusted for the narrative influence from the dividends/earnings unscheduled corporate event group presented in Chapter 7. Cointegration analysis finds that stock market prices and dividends only share a longer-run cointegrating relationship when dividends are adjusted for novelty–narrative effects. The chapter then offers an example applying the baseline KU corporate index interacted with sentiment, novelty, and relevance to a simple trading strategy that shows enhanced returns through a back-testing example where long positions are opened or closed based on moderately high narrative intensity periods.
The dairy industries in California, Idaho, and New Mexico expanded rapidly during the early 2000s. This study focuses on the expansion effects on milk-to-hay price responsiveness. Dairy industry expansion makes hay markets tighter, with less available marketable supply in most periods. The empirical models account for the expansion effect as well as those from hay exports and low stocks-to-use ratios that also cause changes in hay market demand characteristics. The results show that hay-to-milk price responsiveness increased after dairy expansion in all analyzed states. Low stocks-to-use and high exports dampened the responsiveness, but were not statistically significant for all analyzed states.
This paper investigates asset-liability management problems in a continuous-time economy. When the financial market consists of cointegrated risky assets, institutional investors attempt to make profit from the cointegration feature on the one hand, while on the other hand they need to maintain a stable surplus level, that is, the company’s wealth less its liability. Challenges occur when the liability is random and cannot be fully financed or hedged through the financial market. For mean–variance investors, an additional concern is the rational time-consistency issue, which ensures that a decision made in the future will not be restricted by the current surplus level. By putting all these factors together, this paper derives a closed-form feedback equilibrium control for time-consistent mean–variance asset-liability management problems with cointegrated risky assets. The solution is built upon the Hamilton–Jacobi–Bellman framework addressing time inconsistency.
We use linear time series and wavelets approach to study the relationships between U.S. and international prices for corn, soybeans, and cotton. We then compare results obtained with each approach and verify that structural breaks discovered with wavelet analysis match those produced with subsequent partial-period cointegration analysis. We find little evidence that short-term fluctuations between domestic and international prices are stable, while long-term relationships for many price pairs experience distinct structural breaks. We further find that even though China is among the largest importers of U.S. agricultural products, its commodity prices share little or no relationship with those prevailing in U.S. markets.
Pesaran, Shin, and Smith (2001) (PSS) proposed a bounds procedure for testing for the existence of long run cointegrating relationships between a unit root dependent variable ($y_{t}$) and a set of weakly exogenous regressors $\boldsymbol{x}_{t}$ when the analyst does not know whether the independent variables are stationary, unit root, or mutually cointegrated processes. This procedure recognizes the analyst’s uncertainty over the nature of the regressors but not the dependent variable. When the analyst is uncertain whether $y_{t}$ is a stationary or unit root process, the test statistics proposed by PSS are uninformative for inference on the existence of a long run relationship (LRR) between $y_{t}$ and $\boldsymbol{x}_{t}$. We propose the long run multiplier (LRM) test statistic as a means of testing for LRRs without knowing whether the series are stationary or unit roots. Using stochastic simulations, we demonstrate the behavior of the test statistic given uncertainty about the univariate dynamics of both $y_{t}$ and $\boldsymbol{x}_{t}$, illustrate the bounds of the test statistic, and generate small sample and approximate asymptotic critical values for the upper and lower bounds for a range of sample sizes and model specifications. We demonstrate the utility of the bounds framework for testing for LRRs in models of public policy mood and presidential success.
This paper charts the evolution of mainly empirical research at the NIESR over the 1970s and 80s. As was all too evident there were very large discrete technical improvements in data handling and manipulation over this period. Less well appreciated were the effects on the economy of major supply-side shocks coming from the World economy leading to ‘Stagflation’ and, interconnected but somewhat later, in the UK, marked changes in macro policy regime. This latter was strongly influenced by the seminal papers of Lucas (1976) and Sims (1980); both highly critical of the then current practices in macroeconomics, though each having very different intellectual stances. The response in the NIESR was to engage at an early stage in these innovations; applying the mantra that an informed criticism was more efficient than an uninformed one. During this period it became a leader in the econometrics of applied macro modelling under different expectations assumptions, including the rational expectations hypothesis (REH). Throughout, it remained critical of the anti-empirical drift encouraged in the Lucas Critique, criticism borne out more recently by the financial instability of the 1990s and the crisis that followed.
We study the exchange rate effects of monetary policy in a balanced macroeconometric two-country model for the United States and United Kingdom. In contrast to the empirical literature, which consistently treats the domestic and foreign countries unequally in the modeling process, we consider full model feedback, allowing for a thorough analysis of the system dynamics. The problem of model dimensionality is tackled by invoking the approach by Aoki (1981). Assuming country symmetry in the long run allows to decouple the two-country macrodynamics of country averages and differences such that the cointegration analysis can be applied to smaller systems. Second, the econometric modeling is general-to-specific, a graph-theoretic approach for the contemporaneous effects combined with automatic general-to-specific model selection. We find delayed overshooting of the exchange rate in the case of a Bank of England monetary shock but instantaneous response to a Fed shock. Altogether the response is more pronounced in the former case.
We evaluate the effects of climate change on Vietnam's rice market. Results suggest that under a low-emission scenario and without interventions, rice production would drop by as much as 18% by 2030 relative to the 1980–1999 average. Farm and wholesale prices would increase by 1.86%, causing domestic demand to fall by 0.38%. The export sector would experience a rise of 6.94% in export free-on-board prices and a drop of 55.36% in export quantities. Farmers would experience a sales loss of 16.02%, whereas wholesalers would see a sales gain of 1.48%. For exporters, their sales loss would amount to 48.42%.
Farm milk prices tend to be volatile. Dairy farmers, industry pundits, and policymakers further tend to react to price volatility with alarm. One point of concern is the response of retail prices. This study investigates farm-to-retail price transmission in the 2000s for whole milk and Cheddar cheese. Results show that price shocks at the farm gate are transmitted with delay and asymmetry to retail. Differences in the nature of price transmission for whole milk and Cheddar cheese prices are also identified.
Wheat types may be classified according to strength, a baking characteristic. Since the demand for wheat is derived demand, the baking characteristic is directly related to end use. Accordingly, the wheat classes that are used in this study are divided into sub-groups according to strength, that is, strong, medium, and weak wheats. Time-series methods are employed to determine how the different classes of wheats are related within each sub-group. The different wheats under the different sub-groups are found to be substitutes to various degrees, but form a robust cointegrating relationship, implying that the wheat prices in these markets are bound together by a long-term equilibrium relationship. Within each of the sub-groups, the U.S. wheats were found to act as a price leader, driving the prices of other wheats belonging in the same sub-group. These U. S. wheats were found to form no long-run relationship between each other given their distinct end uses. The study highlights the importance of differentiating wheat by end use to specify price linkages more accurately.
Existing empirical evidence on the impact of macroeconomic variables on agriculture remains mixed and inconclusive. This paper re-examines the dynamic relationship between monetary policy variables and agricultural prices using alternative vector autoregression (VAR) type model specifications. Directed acyclic graph theory is proposed as an alternative modeling approach to supplement existing modeling methods. Similar to results in other studies, this study's findings show that over the time period analyzed (1975–2000), changes to money supply as a monetary policy tool had little or no impact on agricultural prices. The primary macroeconomic policy instrument that affects agricultural prices is the exchange rate, which is shown to be directly linked to interest rate, a source of monetary policy shock.
We examine the causal relationships between ethanol production and the agricultural economy and rural incomes in the United States for 1981 through 2010. We use bivariate cointegration and Granger causality procedures and account for two structural breaks in ethanol production in the analysis, which shows that ethanol production Granger-caused agricultural net value added, agriculture's share of U.S. employment, net returns to operators, and rural income per capita in the short run. These causal relationships generally persisted in the long run. However, the causality between ethanol and rural incomes diminished in the long run.
This paper applies cointegration techniques, developed in econometrics to model long-run relationships, to cause-of-death data. We analyze the five main causes of death across five major countries, including USA, Japan, France, England & Wales and Australia. Our analysis provides a better understanding of the long-run equilibrium relationships between the five main causes of death, providing new insights into similarities and differences in trends. The results identify for the first time similarities between countries and genders that are consistent with past studies on the aging processes by biologists and demographers. The insights from biological theory on aging are found to be reflected in the cointegrating relations in all of the countries included in the study.
The U.S. broiler industry is highly vertically integrated and increasingly concentrated in the number of firms and production areas. These structural elements could have implications for performance and the functioning of the law of one price (LOP) across regions. This article investigates this using data on four regional markets. Cointegration results indicate that regional prices are spatially linked in the long run, but pairwise cointegration was not found, suggesting that the LOP does not hold. Causality tests confirm the relative importance of price shocks from the South. This finding is reflective of price coordination by firms with production in multiple regions.
This study analyzes the value of agricultural research to Florida by examining the effect of research spending on agricultural productivity, as measured by a total factor productivity index, and profitability, as measured by net farm income. Results suggest that research expenditures do increase agricultural productivity in the state. However, agricultural productivity does not affect net cash income. Further, the economic rents to the productivity gains do not accrue to land values. Instead, the economic value of research innovations accrues more to consumers than to producers. Thus, consumers are the ultimate beneficiaries of agricultural research in Florida, thereby justifying public funding for agricultural research.
Delineation of geographic markets for fed cattle is essential in monitoring price behavior and determining geographic markets. This study uses transactions data from 28 U.S. fed cattle slaughter plants to determine the extent of the geographic market for fed cattle. Results indicate a national market for fed cattle with prices across most plants cointegrated. In addition, price discovery originates predominantly at plants located in Nebraska, and typically one-third of the total price adjustment to spatial integration occurs in one day.