Bayesian Analysis of DSGE Models with Regime Switching

I estimate DSGE models with recurring regime changes in monetary policy (inflation target and reaction coefficients), technology (growth rate and volatility), and/or nominal price rigidities. In the models, agents are assumed to know deep parameter values but make probabilistic inference about prevailing and future regimes based on Bayes’ rule. I develop an estimation method that takes these probabilistic inferences into account when relating state variables to observed data. In an application to postwar U.S. data, I find stronger support for regime switching in monetary policy than in technology or nominal rigidities. In addition, a model with regime switching policy that conforms to the long-run Taylor principle given in Davig and Leeper (2007) is preferred to a determinacy-indeterminacy model motivated by Lubik and Schorfheide (2004). These empirical results indicate that, even though a passive policy regime produced more volatility in the economy from the early 1970s to the mid-1980s, the economy can be explained by determinacy over the entire postwar period, implying no role for sunspot shocks in explaining the changes in volatility

Bayesian Analysis of DSGE Models with Regime Switching

I estimate DSGE models with recurring regime changes in monetary policy (inflation target and reaction coefficients), technology (growth rate and volatility), and/or nominal price rigidities. In the models, agents are assumed to know deep parameter values but make probabilistic inference about prevailing and future regimes based on Bayes’ rule. I develop an estimation method that takes these probabilistic inferences into account when relating state variables to observed data. In an application to postwar U.S. data, I find stronger support for regime switching in monetary policy than in technology or nominal rigidities. In addition, a model with regime switching policy that conforms to the long-run Taylor principle given in Davig and Leeper (2007) is preferred to a determinacy-indeterminacy model motivated by Lubik and Schorfheide (2004). These empirical results indicate that, even though a passive policy regime produced more volatility in the economy from the early 1970s to the mid-1980s, the economy can be explained by determinacy over the entire postwar period, implying no role for sunspot shocks in explaining the changes in volatility.New Keynesian DSGE; Markov-switching; Monetary Policy; Indeterminacy; Long-run Taylor Principle; Bayesian Analysis;

Renal and Hepatic Dysfunction in Malaria Patients in Minna, North Central Nigeria

Information on kidney and liver involvement in malaria in Africa is still very scanty. Kidney and liver functions were assessed in 70 malaria patients using serum levels of creatinine and urea and urinary protein levels as test indicators of kidney function and serum levels of bilirubin, aspartate aminotranferase (AST or SGOT), alanine aminotransferase (ALT or SGPT), and alkaline phosphatase (ALP) as indicators of liver function. Descriptive analysis of results obtained showed that 67.14% of patients had creatinine level above the 126µmole/L which is considered the upper limit of the normal range. Three cases (4.29%) had creatinine levels well above 265µmoles/L. The serum concentrations of creatinine, urea, protein, conjugated and total bilirubin, AST, ALT, and ALP in malaria patients were significantly higher (p<0.05) than those of malaria free individuals. We conclude that renal dysfunction, acute renal failure and liver dysfunction are clinical features of malaria in Minna, North Central Nigeri

Comparison of Subjective and Objective Physical Functions in Patients with Chronic Low Back Pain

Purpose: To compare the subjective and objective physical function scores of patients with Chronic Low Back Pain (CLBP). Method: A cross- sectional survey design was used. Fifty-one patients with CLBP of mechanical origin were recruited from the physiotherapy out patient clinics of the University of Nigeria Teaching Hospital and the National Orthopedic Hospital both in Enugu, Nigeria. The box numerical scale, Roland-Morris Questionnaire (RMQ-24) and the Back Performance Scale (BPS) were used to assess the present pain intensity, the subjective and objective functional status of the participants respectively. Pearson correlation was used to determine relationships. Multiple Regressions were used to determine the predictors of objective function. Alpha level was set at 0.5. Results: The mean age and Body Mass Index of the participants were 49.04 ± 14.33 years and 26.57 ± 4.29 kg/m2 respectively. The mean Pain Intensity, subjective disability (RMQ) and objective disability (BPS) scores were 6.33 ± 2.09, 9.76 ± 5.14 and 6.43 ± 2.9 respectively. Stepwise multiple regressions showed that when all the variables were entered only marital status was a significant predictor of objective physical function. Conclusion: There is no significant association between subjective and objective functions in patients with CLBP. However, marital status (married) is a significant predictor of objective function in CLBP

Likelihood-Based Confidence Sets for the Timing of Structural Breaks

In this paper, we propose a new approach to constructing confidence sets for the timing of structural breaks. This approach involves using Markov-chain Monte Carlo methods to simulate marginal “fiducial” distributions of break dates from the likelihood function. We compare our proposed approach to asymptotic and bootstrap confidence sets and find that it performs best in terms of producing short confidence sets with accurate coverage rates. Our approach also has the advantages of i) being broadly applicable to different patterns of structural breaks, ii) being computationally efficient, and iii) requiring only the ability to evaluate the likelihood function over parameter values, thus allowing for many possible distributional assumptions for the data. In our application, we investigate the nature and timing of structural breaks in postwar U.S. Real GDP. Based on marginal fiducial distributions, we find much tighter 95% confidence sets for the timing of the so-called “Great Moderation” than has been reported in previous studies.Fiducial Inference; Bootstrap Methods; Structural Breaks; Confidence Intervals and Sets; Coverage Accuracy and Expected Length; Markov-chain Monte Carlo;

Speciation of Heavy Metals in Sediment of Agbabu Bitumen deposit area, Nigeria

Speciation of heavy metals Cu, Cd, Pb, Ni, Zn, Mn, Fe, Cr and Hg was carried out on sediment of Agbabu with a sequential extraction procedure in the dry and rainy seasons of year 2008. Hg was not detected in all the fractions in the two seasons. In the dry season, all the metals were mostly abundant in Fraction-5, however, Cr (30%) and Mn (23.73%) had high abundance in Fraction-1, Zn (30.97%) was high in Fraction-III, Cu (45.14%) and Fe (31.67%) were also high in Fraction-4. In the rainy season, Cr (35.82%) was mostly abundant in Fraction-1, Zn (36.71%) was high in Fraction-3, Cu (29.28%) was high in Fraction-4 and the remaining metals were mostly abundant in Fraction-V. From the results of the two seasons, the metals had high abundance in Fraction-5 indicating firstly, low mobility and bioavailability, secondly, low degree of pollution by the metals considered and thirdly, the origin of the metals in the environment was likely to be lithogenic. The average potential mobility was calculated for the metals in the two seasons and the following decreasing order was obtained: Cr>Zn>Cu>Mn>Fe>Cd>Ni>Pb>Hg. @JASEMJ. Appl. Sci. Environ. Manage. December, 2010, Vol. 14 (4) 47 - 5

AKT activation controls cell survival in response to HDAC6 inhibition.

HDAC6 is emerging as an important therapeutic target for cancer. We investigated mechanisms responsible for survival of tumor cells treated with a HDAC6 inhibitor. Expression of the 20 000 genes examined did not change following HDAC6 treatment in vivo. We found that HDAC6 inhibition led to an increase of AKT activation (P-AKT) in vitro, and genetic knockdown of HDAC6 phenocopied drug-induced AKT activation. The activation of AKT was not observed in PTEN null cells; otherwise, PTEN/PIK3CA expression per se did not predict HDAC6 inhibitor sensitivity. Interestingly, HDAC6 inhibitor treatment led to inactivating phosphorylation of PTEN (P-PTEN Ser380), which likely led to the increased P-AKT in cells that express PTEN. Synergy was observed with phosphatidylinositol 3-kinases (PI3K) inhibitor treatment in vitro, accompanied by increased caspase 3/7 activity. Furthermore, combination of HDAC6 inhibitor with a PI3K inhibitor caused substantial tumor growth inhibition in vivo compared with either treatment alone, also detectable by Ki-67 immunostaining and (18)F-FLT positron emission tomography (PET). In aggregate AKT activation appears to be a key survival mechanism for HDAC6 inhibitor treatment. Our findings indicate that dual inhibition of HDAC6 and P-AKT may be necessary to substantially inhibit growth of solid tumors

Identification of Outlying Observations with Quantile Regression for Censored Data

Outlying observations, which significantly deviate from other measurements, may distort the conclusions of data analysis. Therefore, identifying outliers is one of the important problems that should be solved to obtain reliable results. While there are many statistical outlier detection algorithms and software programs for uncensored data, few are available for censored data. In this article, we propose three outlier detection algorithms based on censored quantile regression, two of which are modified versions of existing algorithms for uncensored or censored data, while the third is a newly developed algorithm to overcome the demerits of previous approaches. The performance of the three algorithms was investigated in simulation studies. In addition, real data from SEER database, which contains a variety of data sets related to various cancers, is illustrated to show the usefulness of our methodology. The algorithms are implemented into an R package OutlierDC which can be conveniently employed in the \proglang{R} environment and freely obtained from CRAN

The Surgical Release of Dupuytren's Contracture Using Multiple Transverse Incisions.

Dupuytren's contracture is a condition commonly encountered by hand surgeons, although it is rare in the Asian population. Various surgical procedures for Dupuytren's contracture have been reported, and the outcomes vary according to the treatment modalities. We report the treatment results of segmental fasciectomies with multiple transverse incisions for patients with Dupuytren's contracture. The cases of seven patients who underwent multiple segmental fasciectomies with multiple transverse incisions for Dupuytren's contracture from 2006 to 2011 were reviewed retrospectively. Multiple transverse incisions to the severe contracture sites were performed initially, and additional incisions to the metacarpophalangeal (MCP) joints, and the proximal interphalangeal (PIP) joints were performed if necessary. Segmental fasciectomies by removing the fibromatous nodules or cords between the incision lines were performed and the wound margins were approximated. The mean range of motion of the involved MCP joints and PIP joints was fully recovered. During the follow-up periods, there was no evidence of recurrence or progression of disease. Multiple transverse incisions for Dupuytren's contracture are technically challenging, and require a high skill level of hand surgeons. However, we achieved excellent correction of contractures with no associated complications. Therefore, segmental fasciectomies with multiple transverse incisions can be a good treatment option for Dupuytren's contracture