When applied to time series processes containing occasional level shifts, the log-periodogram (GPH) estimator often erroneously finds long memory. For a stationary short-memory process with a slowly varying level, I show that the GPH estimator is substantially biased, and I derive an approximation to this bias. The asymptotic bias lies on the (0,1) interval, and its exact value depends on the ratio of the expected number of level shifts to a user-defined bandwidth parameter. Using this result, I formulate the Modified GPH estimator, which has a markedly lower bias. I illustrate this new estimator via applications to soybean prices and stock market volatility.

## Type of Work

Article (22) Book (0) Theses (0) Multimedia (0)

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UC Berkeley (8) UC Davis (19) UC Irvine (0) UCLA (1) UC Merced (0) UC Riverside (8) UC San Diego (1) UCSF (0) UC Santa Barbara (0) UC Santa Cruz (0) UC Office of the President (1) Lawrence Berkeley National Laboratory (1) UC Agriculture & Natural Resources (0)

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Giannini Foundation of Agricultural Economics (8) Department of Agricultural and Resource Economics (7) Department of Economics, UCSD (1) University of California Institute of Transportation Studies (1) UC Davis Institute of Transportation Studies (1)

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Social and Behavioral Sciences (5) Life Sciences (2) Engineering (1)

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## Scholarly Works (22 results)

In commodity futures markets, contracts with various delivery dates trade simultaneously. Applied researchers typically discard the majority of the data and form a single time series by choosing only one price observation per day. This strategy precludes a full understanding of these markets and can induce complicated nonlinear dynamics in the data. In this paper, I introduce the partially overlapping time series (POTS) model to model jointly all traded contracts. The POTS model incorporates time-to-delivery, storability, seasonality, and GARCH effects. I apply the POTS model to corn futures at the Chicago Board of Trade and the results uncover substantial inefficiency associated with delivery on corn futures. The results also support two theories of commodity pricing: the theory of storage and the Samuelson effect.

This article addresses the problem of forecasting time series that are subject to level shifts. Processes with level shifts possess a nonlinear dependence structure. Using the stochastic permanent breaks (STOPBREAK) model, I model this nonlinearity in a direct and flexible way that avoids imposing a discrete regime structure. I apply this model to the rate of price inflation in the United States, which I show is subject to level shifts. These shifts significantly affect the accuracy of out-of-sample forecasts, causing models that assume covariance stationarity to be substantially biased. Models that do not assume covariance stationarity, such as the random walk, are unbiased but lack precision in periods without shifts. I show that the STOPBREAK model outperforms several alternative models in an out-of-sample inflation forecasting experiment.

Genetic modification of crops has revolutionized food production, but it remains controversial due to food safety concerns. A recent food safety scare provides a natural experiment on the market's willingness to accept an increase in perceived risk from genetically modified (GM) food. We analyze the market impact of contamination of the U.S. food-corn supply by a GM variety called StarLink. We find that the contamination led to a 6.8 percent discount in corn prices and that the suppression of prices lasted for at least a year.

This paper aims to bridge the gap between processes where shocks are permanent and those with transitory shocks by formulating a process in which the long run impact of each innovation is time varying and stochastic. Frequent transitory shocks are supplemented by occasional permanent shifts. The stochastic permanent breaks (STOPBREAK) process is based on the premise that a shock is more likely to be permanent if it is large than if it is small. This formulation is motivated by a class of processes that undergo random structural breaks. Consistency and asymptotic normality of quasi maximum likelihood estimates is established and locally best hypothesis tests of the null of a random walk are developed. The model is applied to relative prices of pairs of stocks and significant test statistics result

In Markov-switching regression models, we use Kullback-Leibler (KL) divergence between the true and candidate models to select the number of states and variables simultaneously. In applying Akaike information criterion (AIC), which is an estimate of KL divergence, we find that AIC retains too many states and variables in the model. Hence, we derive a new information criterion, Markov switching criterion (MSC), which yields a marked improvement in state determination and variable selection because it imposes an approriate penalty to mitigate the over-retention of states in the Markov chain. MSC performs well in Monte Carlo studies with single and multiple states, small and large samples, and low and high noise. Furthermore, it not only applies to Markov-switching regression models, but also performs well in Markov-switching autoregression models. Finally, the usefulness of MSC is illustrated via applications to the U.S. business cycle and the effectiveness of media advertising.

**1. Biofuel Policies: Robbing Peter to Pay Paul**

Policies aimed at reducing carbon emissions from transportation have hit major obstacles in the past few years. In effect, these policies take money from petroleum producers and give it to renewable fuel producers, creating heated political and legal battles but little effect on consumers.

**2. Which California Foods You Consume Makes Little Impact on Drought-Relevant Water Usage**

To be relevant to California’s drought, discussions of water used to produce food items should focus on the irrigation water relevant to production in California. By that measure, drought-relevant water used to produce livestock products such as beef and milk is moderate compared to crop products such as wine and broccoli.

**3. Europe's Migration Crisis**

The European Union’s 28 member nations received 1.2 million applications from asylum seekers in 2015. One reason for the upsurge in asylum applicants is that German Chancellor Angela Merkel in August 2015 announced that Syrians could apply for asylum in Germany even if they passed through safe countries en route. The challenges of integrating asylum seekers are becoming clearer, prompting talk of reducing the influx, reforming EU institutions, and integrating migrants.

ARTICLES:

1. Giving an Inch and Keeping a Mile: Why the Corn Lobby Let the Ethanol Tax Credit Expire.

2. The Logic and Consequences of Labeling GMOs.

3. The Alpaca Bubble Revisited.

1. Biofuels Policy in Limbo.

2. Contribution of University of California Cooperative Extension to Drip Irrigation.

3.Farm Labor and Immigration: Outlook for 2015.