Estimation of productivity in Korean electric power plants:a semiparametric smooth coefficient model

This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to model heterogeneous performances across power plants and over time by allowing underlying technologies to be heterogeneous. The SPSC model accommodates both continuous and discrete covariates. Various specification tests are conducted to compare performance of the SPSC model. Using a unique generator level panel dataset spanning the period 1995-2006, we find that the impact of load factor, generator and facility types on power generation varies substantially in terms of magnitude and significance across different plant characteristics. The results have strong implication for generation policy in Korea as outlined in this study.

Estimation of productivity in Korean electric power plants:a semiparametric smooth coefficient model

This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to model heterogeneous performances across power plants and over time by allowing underlying technologies to be heterogeneous. The SPSC model accommodates both continuous and discrete covariates. Various specification tests are conducted to assess the performance of the SPSC model. Using a unique generator level panel dataset spanning the period 1995-2006, we find that the impact of load factor, generator and facility types on power generation varies substantially in terms of magnitude and significance across different plant characteristics. The results have strong implications for generation policy in Korea as outlined in this study.

A Study of Stock Market Fluctuations and their Relations to Business Conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubble-like deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the non-fundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

Essays in Macro Finance

I study the link between capital markets and sources of macroeconomic risk. In chapter 1 I show that expected inflation risk is priced in the cross section of stock returns even after controlling for cash flow growth and volatility risks. Motivated by this evidence I study a long run risk model with a built-in inflation non-neutrality channel that allows me to decompose the real stochastic discount factor into news about current and expected cash flow growth, news about expected inflation and news about volatility. The model can successfully price a broad menu of assets and provides a setting for analyzing cross sectional variation in expected inflation risk premium. For industries like retail and durable goods inflation risk can account for nearly a third of the overall risk premium while the energy industry and a broad commodity index act like inflation hedges. Nominal bonds are exposed to expected inflation risk and have inflation premiums that increase with bond maturity. The price of expected inflation risk was very high during the 70's and 80's, but has come down a lot since being very close to zero over the past decade. On average, the expected inflation price of risk is negative, consistent with the view that periods of high inflation represent a "bad" state of the world and are associated with low economic growth and poor stock market performance. In chapter 2 I look at the way capital markets react to predetermined macroeconomic announcements. I document significantly higher excess returns on the US stock market on macro release dates as compared to days when no macroeconomic news hit the market. Almost the entire equity premium since 1997 is being realized on days when macroeconomic news are released. At high frequency, there is a pattern of returns increasing in the hours prior to the pre-determined announcement time, peaking around the time of the announcement and dropping thereafter.

Stochastic Framework for Strategic Decision-making of Load-serving Entities for Day-ahead Market

The deregulation of electricity markets has diversified the range of financial transaction modes between independent system operator (ISO), generation companies (GENCO) and load-serving entities (LSE) as the main interacting players of a day-ahead market (DAM). LSEs sell electricity to end-users and retail customers. The LSE that owns distributed generation (DG) or energy storage units can supply part of its serving loads when the nodal price of electricity rises. This opportunity stimulates them to have storage or generation facilities at the buses with higher locational marginal prices (LMP). The short-term advantage of this model is reducing the risk of financial losses for LSEs in DAMs and its long-term benefit for the LSEs and the whole system is market power mitigation by virtually increasing the price elasticity of demand. This model also enables the LSEs to manage the financial risks with a stochastic programming framework.

Stochastic Short-term Incentive-based Demand Response Scheduling of Load-serving Entities

In competitive electricity markets it is necessary for a profit-seeking load-serving entity (LSE) to optimally adjust the financial incentives offering the end users that buy electricity at regulated rates to reduce the consumption during high market prices. The LSE in this model manages the demand response (DR) by offering financial incentives to retail customers, in order to maximize its expected profit and reduce the risk of market power experience. The stochastic formulation is implemented into a test system where a number of loads are supplied through LSEs.

IInflation and Globalisation: A Dynamic Factor Model with Stochastic Volatility

National inflation rates reflect domestic and international (regional and global) influences. The relative importance of these components remains a controversial empirical issue. We extend the literature on inflation co-movement by utilising a dynamic factor model with stochastic volatility to account for shifts in the variance of inflation and endogenously determined regional groupings. We find that most of inflation variability is explained by the country specific disturbance term. Nevertheless, the contribution of the global component in explaining industrialised countries’ inflation rates has increased over time.

Development of Preliminary Load and Resistance Factor Design of Drilled Shafts in Iowa, RB03-012, 2014

The Federal Highway Administration (FHWA) mandated utilizing the Load and Resistance Factor Design (LRFD) approach for all new bridges initiated in the United States after October 1, 2007. To achieve part of this goal, a database for Drilled Shaft Foundation Testing (DSHAFT) was developed and reported on by Garder, Ng, Sritharan, and Roling in 2012. DSHAFT is aimed at assimilating high-quality drilled shaft test data from Iowa and the surrounding regions. DSHAFT is currently housed on a project website (http://srg.cce.iastate.edu/dshaft) and contains data for 41 drilled shaft tests. The objective of this research was to utilize the DSHAFT database and develop a regional LRFD procedure for drilled shafts in Iowa with preliminary resistance factors using a probability-based reliability theory. This was done by examining current design and construction practices used by the Iowa Department of Transportation (DOT) as well as recommendations given in the American Association of State Highway and Transportation Officials (AASHTO) LRFD Bridge Design Specifications and the FHWA drilled shaft guidelines. Various analytical methods were used to estimate side resistance and end bearing of drilled shafts in clay, sand, intermediate geomaterial (IGM), and rock. Since most of the load test results obtained from O-cell do not pass the 1-in. top displacement criterion used by the Iowa DOT and the 5% of shaft diameter for top displacement criterion recommended by AASHTO, three improved procedures are proposed to generate and extend equivalent top load-displacement curves that enable the quantification of measured resistances corresponding to the displacement criteria. Using the estimated and measured resistances, regional resistance factors were calibrated following the AASHTO LRFD framework and adjusted to resolve any anomalies observed among the factors. To illustrate the potential and successful use of drilled shafts in Iowa, the design procedures of drilled shaft foundations were demonstrated and the advantages of drilled shafts over driven piles were addressed in two case studies.

Coxsackievirus B3-associated myocardial pathology and viral load reduced by recombinant soluble human decay-accelerating factor in mice

Coxsackievirus B3 (CVB3) infection can result in myocarditis, which in turn may lead to a protracted immune response and subsequent dilated cardiomyopathy. Human decay-accelerating factor (DAF), a binding receptor for CVB3, was synthesized as a soluble IgG1-Fc fusion protein (DAF-Fc). In vitro, DAF-Fc was able to inhibit complement activity and block infection by CVB3, although blockade of infection varied widely among strains of CVB3. To determine the effects of DAF-Fc in vivo, 40 adolescent A/J mice were infected with a myopathic strain of CVB3 and given DAF-Fc treatment 3 days before infection, during infection, or 3 days after infection; the mice were compared with virus alone and sham-infected animals. Sections of heart, spleen, kidney, pancreas, and liver were stained with hematoxylin and eosin and submitted to in situ hybridization for both positive-strand and negative-strand viral RNA to determine the extent of myocarditis and viral infection, respectively. Salient histopathologic features, including myocardial lesion area, cell death, calcification and inflammatory cell infiltration, pancreatitis, and hepatitis were scored without knowledge of the experimental groups. DAF-Fc treatment of mice either preceding or concurrent with CVB3 infection resulted in a significant decrease in myocardial lesion area and cell death and a reduction in the presence of viral RNA. All DAF-Fc treatment groups had reduced infectious CVB3 recoverable from the heart after infection. DAF-Fc may be a novel therapeutic agent for active myocarditis and acute dilated cardiomyopathy if given early in the infectious period, although more studies are needed to determine its mechanism and efficacy.

Simulation-based smoothing and filtering in factor stochastic volatility models : two econometric applications

In this article we use factor models to describe a certain class of covariance structure for financiaI time series models. More specifical1y, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. We build on previous work by allowing the factor loadings, in the factor mo deI structure, to have a time-varying structure and to capture changes in asset weights over time motivated by applications with multi pIe time series of daily exchange rates. We explore and discuss potential extensions to the models exposed here in the prediction area. This discussion leads to open issues on real time implementation and natural model comparisons.

Simulation -based smoothing and filtering in factor stochastic volatility models : two econometric applications (July-2001)

The past decade has wítenessed a series of (well accepted and defined) financial crises periods in the world economy. Most of these events aI,"e country specific and eventually spreaded out across neighbor countries, with the concept of vicinity extrapolating the geographic maps and entering the contagion maps. Unfortunately, what contagion represents and how to measure it are still unanswered questions. In this article we measure the transmission of shocks by cross-market correlation\ coefficients following Forbes and Rigobon's (2000) notion of shift-contagion,. Our main contribution relies upon the use of traditional factor model techniques combined with stochastic volatility mo deIs to study the dependence among Latin American stock price indexes and the North American indexo More specifically, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. From a theoretical perspective, we improve currently available methodology by allowing the factor loadings, in the factor model structure, to have a time-varying structure and to capture changes in the series' weights over time. By doing this, we believe that changes and interventions experienced by those five countries are well accommodated by our models which learns and adapts reasonably fast to those economic and idiosyncratic shocks. We empirically show that the time varying covariance structure can be modeled by one or two common factors and that some sort of contagion is present in most of the series' covariances during periods of economical instability, or crisis. Open issues on real time implementation and natural model comparisons are thoroughly discussed.

Stochastic knock detection model for spark ignited engines

This report presents the development of a Stochastic Knock Detection (SKD) method for combustion knock detection in a spark-ignition engine using a model based design approach. Knock Signal Simulator (KSS) was developed as the plant model for the engine. The KSS as the plant model for the engine generates cycle-to-cycle accelerometer knock intensities following a stochastic approach with intensities that are generated using a Monte Carlo method from a lognormal distribution whose parameters have been predetermined from engine tests and dependent upon spark-timing, engine speed and load. The lognormal distribution has been shown to be a good approximation to the distribution of measured knock intensities over a range of engine conditions and spark-timings for multiple engines in previous studies. The SKD method is implemented in Knock Detection Module (KDM) which processes the knock intensities generated by KSS with a stochastic distribution estimation algorithm and outputs estimates of high and low knock intensity levels which characterize knock and reference level respectively. These estimates are then used to determine a knock factor which provides quantitative measure of knock level and can be used as a feedback signal to control engine knock. The knock factor is analyzed and compared with a traditional knock detection method to detect engine knock under various engine operating conditions. To verify the effectiveness of the SKD method, a knock controller was also developed and tested in a model-in-loop (MIL) system. The objective of the knock controller is to allow the engine to operate as close as possible to its border-line spark-timing without significant engine knock. The controller parameters were tuned to minimize the cycle-to-cycle variation in spark timing and the settling time of the controller in responding to step increase in spark advance resulting in the onset of engine knock. The simulation results showed that the combined system can be used adequately to model engine knock and evaluated knock control strategies for a wide range of engine operating conditions.

HLA-G 14-bp Insertion/Deletion Polymorphism Is a Risk Factor for HTLV-1 Infection

About 95% of HTLV-1 infected patients remain asymptomatic throughout life, and the risk factors associated with the development of related diseases, such as HAM/TSP and ATL, are not fully understood. The human leukocyte antigen-G molecule (HLA-G), a nonclassical HLA class I molecule encoded by MHC, is expressed in several pathological conditions, including viral infection, and is related to immunosuppressive effects that allow the virus-infected cells to escape the antiviral defense of the host. The 14-bp insertion/deletion polymorphism of exon 8 HLA-G gene influences the stability of the transcripts and could be related to HTLV-1-infected cell protection and to the increase of proviral load. The present study analyzed by conventional PCR the 14-bp insertion/deletion polymorphism of exon 8 HLA-G gene in 150 unrelated healthy subjects, 82 HTLV-1 infected patients with symptoms (33 ATL and 49 HAM), and 56 asymptomatic HTLV-1 infected patients (HAC). In addition, the proviral load was determined by quantitative real-time PCR in all infected groups and correlated with 14-bp insertion/deletion genotypes. The heterozygote genotype frequencies were significantly higher in HAM, in the symptomatic group, and in infected patients compared to control (p < 0.05). The proviral load was higher in the symptomatic group than the HAC group (p < 0.0005). The comparison of proviral load and genotypes showed that -14-bp/-14-bp genotype had a higher proviral load than +14-bp/-14-bp and +14-bp/+14-bp genotypes. Although HLA-G 14-bp polymorphism does not appear to be associated

Chronic methionine load-induced hyperhomocysteinemia impairs the relaxation induced by bradykinin in the isolated rat carotid

This study investigates the effects of chronic methionine intake on bradykinin (BK)-relaxation. Vascular reactivity experiments were performed on carotid rings from male Wistar rats. Treatment with methionine (0.1, 1 or 2 g kg(-1) per day) for 8 and 16 weeks, but not for 2 and 4 weeks, reduced the relaxation induced by BK. Indomethacin, a non-selective cyclooxygenase (COX) inhibitor, and SQ29548, a selective thromboxane A(2) (TXA(2))/prostaglandin H(2) (PGH(2)) receptor antagonist prevented the reduction in BK-relaxation observed in the carotid from methionine-treated rats. Conversely, AH6809, a selective prostaglandin F(2 alpha) (PGF(2 alpha)) receptor antagonist did not alter BK-relaxation in the carotid from methionine-treated rats. The nitric oxide synthase (NOS) inhibitors L-NAME, L-NNA and 7-nitroindazole reduced the relaxation induced by BK in carotids from control and methionine-treated rats. In summary, we found that chronic methionine intake impairs the endothelium-dependent relaxation induced by BK and this effect is due to an increased production of endothelial vasoconstrictor prostanoids (possibly TXA(2)) that counteracts the relaxant action displayed by the peptide.