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Recent advances in perovskite ferroelectrics have fostered a host of exciting sensors and actuators. Defect engineering provides critical control of the performance of ferroelectric materials, especially lead‐free ones. However, it remains a challenge to quantitatively study the concentration of defects due to the complexity of measurement techniques. Here, a feasible approach to analyzing the A‐site defect and electron in alkali metal niobate is demonstrated. The theoretical relationships among defect concentration, conductivity, and oxygen partial pressure can be established based on the defect chemistry equilibria. The type and concentration of defects are reflected through the conductivity variation with oxygen partial pressure. As a result, the variation of defect concentration gives rise to defect‐driven interfacial polarization, which further leads to distinct properties of the ceramics. e.g., abnormal dielectric behavior. Furthermore, this study also suggests a strategy to manipulate defects and charges in perovskite oxides for performance optimization.

Recent advances in perovskite ferroelectrics have fostered a host of exciting sensors and actuators. Defect engineering provides critical control of the performance of ferroelectric materials, especially lead‐free ones. However, it remains a challenge to quantitatively study the concentration of defects due to the complexity of measurement techniques. Here, a feasible approach to analyzing the A‐site defect and electron in alkali metal niobate is demonstrated. The theoretical relationships among defect concentration, conductivity, and oxygen partial pressure can be established based on the defect chemistry equilibria. The type and concentration of defects are reflected through the conductivity variation with oxygen partial pressure. As a result, the variation of defect concentration gives rise to defect‐driven interfacial polarization, which further leads to distinct properties of the ceramics. e.g., abnormal dielectric behavior. Furthermore, this study also suggests a strategy to manipulate defects and charges in perovskite oxides for performance optimization.

Recent advances in perovskite ferroelectrics have fostered a host of exciting sensors and actuators. Defect engineering provides critical control of the performance of ferroelectric materials, especially lead‐free ones. However, it remains a challenge to quantitatively study the concentration of defects due to the complexity of measurement techniques. Here, a feasible approach to analyzing the A‐site defect and electron in alkali metal niobate is demonstrated. The theoretical relationships among defect concentration, conductivity, and oxygen partial pressure can be established based on the defect chemistry equilibria. The type and concentration of defects are reflected through the conductivity variation with oxygen partial pressure. As a result, the variation of defect concentration gives rise to defect‐driven interfacial polarization, which further leads to distinct properties of the ceramics. e.g., abnormal dielectric behavior. Furthermore, this study also suggests a strategy to manipulate defects and charges in perovskite oxides for performance optimization.

Recent advances in perovskite ferroelectrics have fostered a host of exciting sensors and actuators. Defect engineering provides critical control of the performance of ferroelectric materials, especially lead‐free ones. However, it remains a challenge to quantitatively study the concentration of defects due to the complexity of measurement techniques. Here, a feasible approach to analyzing the A‐site defect and electron in alkali metal niobate is demonstrated. The theoretical relationships among defect concentration, conductivity, and oxygen partial pressure can be established based on the defect chemistry equilibria. The type and concentration of defects are reflected through the conductivity variation with oxygen partial pressure. As a result, the variation of defect concentration gives rise to defect‐driven interfacial polarization, which further leads to distinct properties of the ceramics. e.g., abnormal dielectric behavior. Furthermore, this study also suggests a strategy to manipulate defects and charges in perovskite oxides for performance optimization.

The aim of this paper is to establish a causal link between the policies implemented by technology companies and the outcomes they yield within intricate temporal and/or spatial dependent experiments. We propose a novel temporal/spatio-temporal Varying Coefficient Decision Process (VCDP) model, capable of effectively capturing the evolving treatment effects in situations characterized by temporal and/or spatial dependence. Our methodology encompasses the decomposition of the Average Treatment Effect (ATE) into the Direct Effect (DE) and the Indirect Effect (IE). We subsequently devise comprehensive procedures for estimating and making inferences about both DE and IE. Additionally, we provide a rigorous analysis of the statistical properties of these procedures, such as asymptotic power. To substantiate the effectiveness of our approach, we carry out extensive simulations and real data analyses.

There has been a surge of interest in developing robust estimators for models with heavy-tailed and bounded variance data in statistics and machine learning, while few works impose unbounded variance. This paper proposes two type of robust estimators, the ridge log-truncated M-estimator and the elastic net log-truncated M-estimator. The first estimator is applied to convex regressions such as quantile regression and generalized linear models, while the other one is applied to high dimensional non-convex learning problems such as regressions via deep neural networks. Simulations and real data analysis demonstrate the {robustness} of log-truncated estimations over standard estimations., Comment: 44 pages

Yao-Fang Liu, 1 Zheng Fu, 1 Shao-Wei Chen, 1 Xiao-Ping He, 2 Ling-Ye Fan 1 1Department of Reproductive Technology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, People’s Republic of China; 2Department of Prosthodontics, The Affiliated Stomatological Hospital of Southwest Medical University, Luzhou, 646000, People’s Republic of ChinaCorrespondence: Ling-Ye FanDepartment of Reproductive Technology, The Affiliated Hospital of Southwest Medical University, No. 25 of Taiping Street, Jiangyang District, Luzhou, 646000, People’s Republic of ChinaTel/Fax +86 0830 3165649Email lingyefan_cnsd@163.comBackground: This study aimed to examine the differences in anxiety and depression between infertile Chinese couples in diverse stages of in vitro fertilization-embryo transfer (IVF-ET) and their relationship with the IVF-ET outcomes.Methods: From February 2016 to December 2018, a total of 247 couples that were undergoing IVF-ET were randomly selected for this study. On the day they started their treatment (T1), the day human chorionic gonadotropin was administered (T2), and 4 days after the embryo transfer (T3), self-designed questionnaires, the Self-Rating Anxiety Scale, and the Self-Rating Depression Scale were completed to investigate anxiety and depression in different stages.Results: Age had an effect on the anxiety and depression in women. Male infertility type and the cause of infertility had an effect on the anxiety and depression in men. The incidence of anxiety in women in the T1, T2, and T3 stages was 29.96%, 44.94%, and 17.81%, respectively. The anxiety scores of women were 46.14 ± 8.37, 50.83 ± 8.50, and 44.09 ± 8.17, respectively, which were significantly higher than those of men (p < 0.05). The anxiety score in stage T2 was the highest in women, and the depression score of women in stage T1 was the highest. The incidence of anxiety in men in the T1, T2, and T3 stages was

Bayes classifiers for functional data pose a challenge. This is because probability density functions do not exist for functional data. As a consequence, the classical Bayes classifier using density quotients needs to be modified. We propose to use density ratios of projections on a sequence of eigenfunctions that are common to the groups to be classified. The density ratios can then be factored into density ratios of individual functional principal components whence the classification problem is reduced to a sequence of nonparametric one-dimensional density estimates. This is an extension to functional data of some of the very earliest nonparametric Bayes classifiers that were based on simple density ratios in the one-dimensional case. By means of the factorization of the density quotients the curse of dimensionality that would otherwise severely affect Bayes classifiers for functional data can be avoided. We demonstrate that in the case of Gaussian functional data, the proposed functional Bayes classifier reduces to a functional version of the classical quadratic discriminant. A study of the asymptotic behavior of the proposed classifiers in the large sample limit shows that under certain conditions the misclassification rate converges to zero, a phenomenon that has been referred to as "perfect classification". The proposed classifiers also perform favorably in finite sample applications, as we demonstrate in comparisons with other functional classifiers in simulations and various data applications, including wine spectral data, functional magnetic resonance imaging (fMRI) data for attention deficit hyperactivity disorder (ADHD) patients, and yeast gene expression data.

Bayes classifiers for functional data pose a challenge. This is because probability density functions do not exist for functional data. As a consequence, the classical Bayes classifier using density quotients needs to be modified. We propose to use density ratios of projections on a sequence of eigenfunctions that are common to the groups to be classified. The density ratios can then be factored into density ratios of individual functional principal components whence the classification problem is reduced to a sequence of nonparametric one-dimensional density estimates. This is an extension to functional data of some of the very earliest nonparametric Bayes classifiers that were based on simple density ratios in the one-dimensional case. By means of the factorization of the density quotients the curse of dimensionality that would otherwise severely affect Bayes classifiers for functional data can be avoided. We demonstrate that in the case of Gaussian functional data, the proposed functional Bayes classifier reduces to a functional version of the classical quadratic discriminant. A study of the asymptotic behavior of the proposed classifiers in the large sample limit shows that under certain conditions the misclassification rate converges to zero, a phenomenon that has been referred to as "perfect classification". The proposed classifiers also perform favorably in finite sample applications, as we demonstrate in comparisons with other functional classifiers in simulations and various data applications, including wine spectral data, functional magnetic resonance imaging (fMRI) data for attention deficit hyperactivity disorder (ADHD) patients, and yeast gene expression data.

Background: Gastric cancer is the second highest cause of cancer deaths worldwide. Apart from Japan and Korea where screening programs are implemented, most gastric cancer patients worldwide are diagnosed at an advanced stage because of limited knowledge and experience of endoscopists. An internet-based e-learning system to teach detection of early gastric cancer using standard endoscopy has been developed and this study evaluated its effectiveness. Methods: The study was designed as a randomized controlled trial. Participants worldwide signed a consent form before first undertaking a pre-test via the internet, after which they were randomly allocated to the e-learning and non-e-learning groups. Pre-adjustment strata were the pre-test score, experience of endoscopy, being a nurse endoscopist or a medical practitioner, and medical institution and country. Only the participants in the e-learning group were allowed to access the e-learning system, which consisted of video lectures on basic knowledge and self-exercise tests to accumulate experience. A post-test in both groups was conducted 2 months after the pre-test. The pre-determined primary endpoint was the difference in the rate of improvement of the test result (post-test score/pre-test score) between groups. After completion of the post-test, the e-learning system was opened for all participants. Results: Among the 515 endoscopists from 35 countries assessed for eligibility, 322 participants who met the study’s inclusion criteria completed the pre-test and were enrolled: 166 were allocated to the e-learning group and 166 to the non-e-learning. Of these, 151 participants in the e-learning group and 144 in the non-e-learning group completed the post-test, and were included in the analysis. The mean rate of improvement (standard deviation) of the test result in the e-learning and non-elearning groups was 1.24 (0.26) and. 1.00 (0.16), respectively (P!0.001, Student’s ttest). Conclusion: This global study clearly demo, Trabajo presentado en el DDW2015 Digestive Disease Week (DDW 2015), desarrolado del 16 al 19 de Mayo, 2015 en la ciudad de Washington DC, EE.UU

Background: Gastric cancer is the second highest cause of cancer deaths worldwide. Apart from Japan and Korea where screening programs are implemented, most gastric cancer patients worldwide are diagnosed at an advanced stage because of limited knowledge and experience of endoscopists. An internet-based e-learning system to teach detection of early gastric cancer using standard endoscopy has been developed and this study evaluated its effectiveness. Methods: The study was designed as a randomized controlled trial. Participants worldwide signed a consent form before first undertaking a pre-test via the internet, after which they were randomly allocated to the e-learning and non-e-learning groups. Pre-adjustment strata were the pre-test score, experience of endoscopy, being a nurse endoscopist or a medical practitioner, and medical institution and country. Only the participants in the e-learning group were allowed to access the e-learning system, which consisted of video lectures on basic knowledge and self-exercise tests to accumulate experience. A post-test in both groups was conducted 2 months after the pre-test. The pre-determined primary endpoint was the difference in the rate of improvement of the test result (post-test score/pre-test score) between groups. After completion of the post-test, the e-learning system was opened for all participants. Results: Among the 515 endoscopists from 35 countries assessed for eligibility, 322 participants who met the study’s inclusion criteria completed the pre-test and were enrolled: 166 were allocated to the e-learning group and 166 to the non-e-learning. Of these, 151 participants in the e-learning group and 144 in the non-e-learning group completed the post-test, and were included in the analysis. The mean rate of improvement (standard deviation) of the test result in the e-learning and non-elearning groups was 1.24 (0.26) and. 1.00 (0.16), respectively (P!0.001, Student’s ttest). Conclusion: This global study clearly demo, Trabajo presentado en el DDW2015 Digestive Disease Week (DDW 2015), desarrolado del 16 al 19 de Mayo, 2015 en la ciudad de Washington DC, EE.UU

Chunyang Du,1,2,* Yonghong Shi,1,2,* Yunzhuo Ren,1,2 Haijiang Wu,1,2 Fang Yao,1,2 Jinying Wei,1,2 Ming Wu,1,2 Yanjuan Hou,1,2 Huijun Duan1,2 1Department of Pathology, Hebei Medical University, Shijiazhuang, People’s Republic of China; 2Hebei Key Laboratory of Kidney Diseases, Shijiazhuang, People’s Republic of China *These authors contributed equally to this work Abstract: The dysregulation of cholesterol metabolism and inflammation plays a significant role in the progression of diabetic nephropathy (DN). Anthocyanins are polyphenols widely distributed in food and exert various biological effects including antioxidative, anti-inflammatory, and antihyperlipidemic effects. However, it remains unclear whether anthocyanins are associated with DN, and the mechanisms involved in the reciprocal regulation of inflammation and cholesterol efflux are yet to be elucidated. In this study, we evaluated the regulation of cholesterol metabolism and the anti-inflammatory effects exerted by anthocyanins (cyanidin-3-O-β-glucoside chloride [C3G] or cyanidin chloride [Cy]) and investigated the underlying molecular mechanism of action using high-glucose (HG)-stimulated HK-2 cells. We found that anthocyanins enhanced cholesterol efflux and ABCA1 expression markedly in HK-2 cells. In addition, they increased peroxisome proliferator-activated receptor alpha (PPARα) and liver X receptor alpha (LXRα) expression and decreased the HG-induced expression of the proinflammatory cytokines intercellular adhesion molecule-1 (ICAM1), monocyte chemoattractant protein-1 (MCP1), and transforming growth factor-β1 (TGFβ1), as well as NFκB activation. Incubation with the PPARα-specific inhibitor GW6471 and LXRα shRNA attenuated the anthocyanin-mediated promotion of ABCA1 expression and cholesterol efflux, suggesting that anthocyanins activated PPARα-LXRα-ABCA1-dependent cholesterol efflux in

Coal mine ventilator is an important part of the mine work. It can provide a good environment to ensure the miners' personnel body health and life safety. Emergency Power Supply system also says EPS; it is a standby power when the mine ventilator has no power. It uses battery pack as energy storage equipment. Therefore, in order to ensure the battery pack has a good charging state, it is very important to develop a big power and high voltage battery pack and improve the charging and discharging control mode and the charging and discharging parameters. This paper studies the battery charging control system and shows the charging working principle of the EPS battery pack, so it puts forward a new type of storage battery charging control technology. © 2014 WIT Press.

The characteristics of dynamic contact resistance reflect the performance and reliability of the whole electromagnetic relay in the electromagnetic relay closing process. Pattern clustering and recognition for electrical contact performance parameters can help diagnose degraded mode, which has a very important significance. Clustering analysis based on

Coal mine ventilator is an important part of the mine work. It can provide a good environment to ensure the miners' personnel body health and life safety. Emergency Power Supply system also says EPS; it is a standby power when the mine ventilator has no power. It uses battery pack as energy storage equipment. Therefore, in order to ensure the battery pack has a good charging state, it is very important to develop a big power and high voltage battery pack and improve the charging and discharging control mode and the charging and discharging parameters. This paper studies the battery charging control system and shows the charging working principle of the EPS battery pack, so it puts forward a new type of storage battery charging control technology. © 2014 WIT Press.

The characteristics of dynamic contact resistance reflect the performance and reliability of the whole electromagnetic relay in the electromagnetic relay closing process. Pattern clustering and recognition for electrical contact performance parameters can help diagnose degraded mode, which has a very important significance. Clustering analysis based on

Coal mine ventilator is an important part of the mine work. It can provide a good environment to ensure the miners' personnel body health and life safety. Emergency Power Supply system also says EPS; it is a standby power when the mine ventilator has no power. It uses battery pack as energy storage equipment. Therefore, in order to ensure the battery pack has a good charging state, it is very important to develop a big power and high voltage battery pack and improve the charging and discharging control mode and the charging and discharging parameters. This paper studies the battery charging control system and shows the charging working principle of the EPS battery pack, so it puts forward a new type of storage battery charging control technology. © 2014 WIT Press.

With the three-dimensional field analysis software Ansoft Maxwell 3D, the three-dimensional finite element model of the contacts pair is established. They belong to a kind of miniature circuit breaker. The simulation is carried out in the transient magnetic field. Under the condition with or without eddy current effect, we get the position and numerical solution of the contact mechanism heat loss under different short-circuit current. © (2013) Trans Tech Publications, Switzerland.

This article develops the automatic test system of voltage and current dynamic waveform for circuit breaker. The system has the automatic monitoring, the storage and the display function of contact voltage and current waveform of circuit breaker in switching process. And then, it also designs the hardware and software of voltage and current dynamic monitoring system for miniature circuit breaker: the hardware circuit of this test system mainly consists of the detection circuit and the data acquisition circuit of current and voltage. And the software system, which mainly consists of control program, data acquisition program and data processing program, is programmed under the condition of LabVIEW. At last, it carries on the real-time monitor to the voltage and current waveform at the both ends of the circuit breaker, especially for the waveform during the switching process, which contributes to study the arc energy and contact wear of circuit breaker. © (2013) Trans Tech Publications, Switzerland.

This article develops the automatic test system of voltage and current dynamic waveform for circuit breaker. The system has the automatic monitoring, the storage and the display function of contact voltage and current waveform of circuit breaker in switching process. And then, it also designs the hardware and software of voltage and current dynamic monitoring system for miniature circuit breaker: the hardware circuit of this test system mainly consists of the detection circuit and the data acquisition circuit of current and voltage. And the software system, which mainly consists of control program, data acquisition program and data processing program, is programmed under the condition of LabVIEW. At last, it carries on the real-time monitor to the voltage and current waveform at the both ends of the circuit breaker, especially for the waveform during the switching process, which contributes to study the arc energy and contact wear of circuit breaker. © (2013) Trans Tech Publications, Switzerland.

With the three-dimensional field analysis software Ansoft Maxwell 3D, the three-dimensional finite element model of the contacts pair is established. They belong to a kind of miniature circuit breaker. The simulation is carried out in the transient magnetic field. Under the condition with or without eddy current effect, we get the position and numerical solution of the contact mechanism heat loss under different short-circuit current. © (2013) Trans Tech Publications, Switzerland.

This article develops the automatic test system of voltage and current dynamic waveform for circuit breaker. The system has the automatic monitoring, the storage and the display function of contact voltage and current waveform of circuit breaker in switching process. And then, it also designs the hardware and software of voltage and current dynamic monitoring system for miniature circuit breaker: the hardware circuit of this test system mainly consists of the detection circuit and the data acquisition circuit of current and voltage. And the software system, which mainly consists of control program, data acquisition program and data processing program, is programmed under the condition of LabVIEW. At last, it carries on the real-time monitor to the voltage and current waveform at the both ends of the circuit breaker, especially for the waveform during the switching process, which contributes to study the arc energy and contact wear of circuit breaker. © (2013) Trans Tech Publications, Switzerland.

With the three-dimensional field analysis software Ansoft Maxwell 3D, the three-dimensional finite element model of the contacts pair is established. They belong to a kind of miniature circuit breaker. The simulation is carried out in the transient magnetic field. Under the condition with or without eddy current effect, we get the position and numerical solution of the contact mechanism heat loss under different short-circuit current. © (2013) Trans Tech Publications, Switzerland.

We demonstrate that the processes underlying on-line auction price bids and many other longitudinal data can be represented by an empirical first order stochastic ordinary differential equation with time-varying coefficients and a smooth drift process. This equation may be empirically obtained from longitudinal observations for a sample of subjects and does not presuppose specific knowledge of the underlying processes. For the nonparametric estimation of the components of the differential equation, it suffices to have available sparsely observed longitudinal measurements which may be noisy and are generated by underlying smooth random trajectories for each subject or experimental unit in the sample. The drift process that drives the equation determines how closely individual process trajectories follow a deterministic approximation of the differential equation. We provide estimates for trajectories and especially the variance function of the drift process. At each fixed time point, the proposed empirical dynamic model implies a decomposition of the derivative of the process underlying the longitudinal data into a component explained by a linear component determined by a varying coefficient function dynamic equation and an orthogonal complement that corresponds to the drift process. An enhanced perturbation result enables us to obtain improved asymptotic convergence rates for eigenfunction derivative estimation and consistency for the varying coefficient function and the components of the drift process. We illustrate the differential equation with an application to the dynamics of on-line auction data.

We demonstrate that the processes underlying on-line auction price bids and many other longitudinal data can be represented by an empirical first order stochastic ordinary differential equation with time-varying coefficients and a smooth drift process. This equation may be empirically obtained from longitudinal observations for a sample of subjects and does not presuppose specific knowledge of the underlying processes. For the nonparametric estimation of the components of the differential equation, it suffices to have available sparsely observed longitudinal measurements which may be noisy and are generated by underlying smooth random trajectories for each subject or experimental unit in the sample. The drift process that drives the equation determines how closely individual process trajectories follow a deterministic approximation of the differential equation. We provide estimates for trajectories and especially the variance function of the drift process. At each fixed time point, the proposed empirical dynamic model implies a decomposition of the derivative of the process underlying the longitudinal data into a component explained by a linear component determined by a varying coefficient function dynamic equation and an orthogonal complement that corresponds to the drift process. An enhanced perturbation result enables us to obtain improved asymptotic convergence rates for eigenfunction derivative estimation and consistency for the varying coefficient function and the components of the drift process. We illustrate the differential equation with an application to the dynamics of on-line auction data.

In dieser Arbeit werden die Folgen der Calvo-Annahme in dynamischen makroökonomischen Modellen untersucht. Dafür wird die Calvo-Annahme unter Anwendung des Konzepts der statistischen Hazardfunktion verallgemeinert. Ich untersuche zwei mögliche Anwendungen dieses Ansatzes innerhalb von DSGE-Modellen. Im ersten Artikel zeige ich, dass der Zugewinn an Handhabbarkeit, der aus der Calvo-Annahme für Neu-Keynesianische Modelle folgt, mit unerwünschten Folgen in Bezug auf die Inflationsdynamiken einher geht. Der zweite Artikel schätzt die aggregierte Hazardfunktion unter Verwendung des theoretischen Rahmens des ersten Artikels. Es zeigt sich, dass die Annahme einer konstanten Hazardfunktion, die aus der Calvo-Annahme folgt, von den Daten eindeutig abgelehnt wird. Im dritten Artikel analysiere ich die Implikationen der empirisch geschätzten Hazardfunktion für die Persistenz von Inflation und die Geldpolitik. Die Untersuchungen zeigen, dass mittels der empirisch plausiblen aggregierten Hazardfunktion Zeitreihen simuliert werden können, die mit der Persistenz der inflatorischen Lücke im US Verbraucherpreisindex konsistent sind. Anhand dieser Ergebnisse komme ich zu dem Schluss, dass die Hazardfunktion eine entscheidende Rolle für die dynamischen Eigenschaften von Inflation spielt. Der letzte Artikel wendet den selben Modellierungsansatz auf ein Real-Business-Cycle Model mit rigidem Arbeitsmarkt an. Unter Verwendung eines allgemeineren stochastischen Anpassungsprozess stelle ich fest, dass die Arbeitsmarktdynamiken von einem Parameter beinflusst werden, der das Monotonieverhalten der Hazardfunktion bestimmt. Insbesondere steigt die Volatilität des Beschäftigungsniveaus, wohingegen dessen Persistenz mit zunehmendem Parameterwert abnimmt., The Calvo assumption (Calvo, 1983) is widely used in the macroeconomic literature to model market frictions that limit the ability of economic agents to re-optimize their control variables. In spite of its virtues, the Calvo assumption also implies singular adjustment behavior at the firm level as well as a restrictive aggregation mechanism for the whole economy. In this study, I examine implications of the Calvo assumption for macroeconomic dynamics. To do so, I extend the Calvo assumption to a more general case based on the concept of the statistical hazard function. Two applications of this approach are studied in the DSGE framework. In the first essay, I apply this approach to a New Keynesian model, and demonstrate that tractability gained from the Calvo pricing assumption is costly in terms of inflation dynamics. The second essay estimates aggregate price reset hazard function using the theoretical framework constructed in the first essay, and shows that the constant hazard function implied by the Calvo assumption is strongly rejected by the aggregate data. In the third essay, I further explore implications of the empirically based hazard function for inflation persistence and monetary policy. I find that the empirically plausible aggregate price reset hazard function can generate simulated data that are consistent with inflation gap persistence found in the US CPI data. Based on these results, I conclude that the price reset hazard function plays a crucial role for generating inflation dynamics. The last essay applies the same modeling approach to a RBC model with employment rigidity. I find that, when introducing a more general stochastic adjustment process, the employment dynamics vary with a parameter, which determines the monotonic property of the hazard function. In particular, the volatility of employment is increasing, but the persistence is decreasing in the value of the parameter.

This paper presents a new mechanism through which monetary policy rules affect inflation persistence. When assuming that price reset hazard functions are not constant, backward- looking dynamics emerge in the NKPC. This new mechanism makes the traditional demand channel of monetary transmission have a long-lasting effect on inflation dynamics. The Calvo model fails to convey this insight, because its constant hazard function leads those important backward-looking dynamics to be canceled out. I first analytically show how it works in a simple setup, and then solve a log-linearized model numerically around positive trend inflation. With realistic calibration of trend inflation and the monetary policy rule, the model can account for the pattern of changes in inflation persistence observed in the post-wwii U.S. data. In addition, with increasing hazard functions, the "Taylor principle" is sufficient to guarantee the determinate equilibrium even under extremely high trend inflation.

This paper presents a new mechanism through which monetary policy rules affect inflation persistence. When assuming that price reset hazard functions are not constant, backward- looking dynamics emerge in the NKPC. This new mechanism makes the traditional demand channel of monetary transmission have a long-lasting effect on inflation dynamics. The Calvo model fails to convey this insight, because its constant hazard function leads those important backward-looking dynamics to be canceled out. I first analytically show how it works in a simple setup, and then solve a log-linearized model numerically around positive trend inflation. With realistic calibration of trend inflation and the monetary policy rule, the model can account for the pattern of changes in inflation persistence observed in the post-wwii U.S. data. In addition, with increasing hazard functions, the "Taylor principle" is sufficient to guarantee the determinate equilibrium even under extremely high trend inflation.

In dieser Arbeit werden die Folgen der Calvo-Annahme in dynamischen makroökonomischen Modellen untersucht. Dafür wird die Calvo-Annahme unter Anwendung des Konzepts der statistischen Hazardfunktion verallgemeinert. Ich untersuche zwei mögliche Anwendungen dieses Ansatzes innerhalb von DSGE-Modellen. Im ersten Artikel zeige ich, dass der Zugewinn an Handhabbarkeit, der aus der Calvo-Annahme für Neu-Keynesianische Modelle folgt, mit unerwünschten Folgen in Bezug auf die Inflationsdynamiken einher geht. Der zweite Artikel schätzt die aggregierte Hazardfunktion unter Verwendung des theoretischen Rahmens des ersten Artikels. Es zeigt sich, dass die Annahme einer konstanten Hazardfunktion, die aus der Calvo-Annahme folgt, von den Daten eindeutig abgelehnt wird. Im dritten Artikel analysiere ich die Implikationen der empirisch geschätzten Hazardfunktion für die Persistenz von Inflation und die Geldpolitik. Die Untersuchungen zeigen, dass mittels der empirisch plausiblen aggregierten Hazardfunktion Zeitreihen simuliert werden können, die mit der Persistenz der inflatorischen Lücke im US Verbraucherpreisindex konsistent sind. Anhand dieser Ergebnisse komme ich zu dem Schluss, dass die Hazardfunktion eine entscheidende Rolle für die dynamischen Eigenschaften von Inflation spielt. Der letzte Artikel wendet den selben Modellierungsansatz auf ein Real-Business-Cycle Model mit rigidem Arbeitsmarkt an. Unter Verwendung eines allgemeineren stochastischen Anpassungsprozess stelle ich fest, dass die Arbeitsmarktdynamiken von einem Parameter beinflusst werden, der das Monotonieverhalten der Hazardfunktion bestimmt. Insbesondere steigt die Volatilität des Beschäftigungsniveaus, wohingegen dessen Persistenz mit zunehmendem Parameterwert abnimmt., The Calvo assumption (Calvo, 1983) is widely used in the macroeconomic literature to model market frictions that limit the ability of economic agents to re-optimize their control variables. In spite of its virtues, the Calvo assumption also implies singular adjustment behavior at the firm level as well as a restrictive aggregation mechanism for the whole economy. In this study, I examine implications of the Calvo assumption for macroeconomic dynamics. To do so, I extend the Calvo assumption to a more general case based on the concept of the statistical hazard function. Two applications of this approach are studied in the DSGE framework. In the first essay, I apply this approach to a New Keynesian model, and demonstrate that tractability gained from the Calvo pricing assumption is costly in terms of inflation dynamics. The second essay estimates aggregate price reset hazard function using the theoretical framework constructed in the first essay, and shows that the constant hazard function implied by the Calvo assumption is strongly rejected by the aggregate data. In the third essay, I further explore implications of the empirically based hazard function for inflation persistence and monetary policy. I find that the empirically plausible aggregate price reset hazard function can generate simulated data that are consistent with inflation gap persistence found in the US CPI data. Based on these results, I conclude that the price reset hazard function plays a crucial role for generating inflation dynamics. The last essay applies the same modeling approach to a RBC model with employment rigidity. I find that, when introducing a more general stochastic adjustment process, the employment dynamics vary with a parameter, which determines the monotonic property of the hazard function. In particular, the volatility of employment is increasing, but the persistence is decreasing in the value of the parameter.

Whelan (2007) found that the generalized Calvo-sticky-price model fails to replicate a typical feature of the empirical reduced-form Phillips curve - the positive dependence of inflation on its own lags. In this paper, I show hat it is the 4-period-Taylor-contract hazard function he chose that gives rise to this result. In contrast, an empirically-based aggregate price reset hazard function can generate simulated data that are consistent with inflation gap persistence found in US CPI data. I conclude that a non-constant price reset hazard plays a crucial role for generating realistic inflation dynamics.

This paper presents an approach to identify aggregate price reset hazards from the joint dynamic behavior of inflation and macroeconomic aggregates. The identification is possible due to the fact that inflation is composed of current and past reset prices and that the composition depends on the price reset hazard function. The derivation of the generalized NKPC links those compostion effects to the hazard function, so that only aggregate data is needed to extract information about the price reset hazard function. The empirical hazard function is generally increasing with the age of prices, but with spikes at the 1st and 4th quarters. The implication of this finding for sticky price modeling is that the pricing decision is characterized by both time- and state-dependent aspects.

Whelan (2007) found that the generalized Calvo-sticky-price model fails to replicate a typical feature of the empirical reduced-form Phillips curve - the positive dependence of inflation on its own lags. In this paper, I show hat it is the 4-period-Taylor-contract hazard function he chose that gives rise to this result. In contrast, an empirically-based aggregate price reset hazard function can generate simulated data that are consistent with inflation gap persistence found in US CPI data. I conclude that a non-constant price reset hazard plays a crucial role for generating realistic inflation dynamics.

This paper presents an approach to identify aggregate price reset hazards from the joint dynamic behavior of inflation and macroeconomic aggregates. The identification is possible due to the fact that inflation is composed of current and past reset prices and that the composition depends on the price reset hazard function. The derivation of the generalized NKPC links those compostion effects to the hazard function, so that only aggregate data is needed to extract information about the price reset hazard function. The empirical hazard function is generally increasing with the age of prices, but with spikes at the 1st and 4th quarters. The implication of this finding for sticky price modeling is that the pricing decision is characterized by both time- and state-dependent aspects.

This paper explores implications of nominal rigidity characterized by a non-constant hazard function for aggregate dynamics. I derive the NKPC under an arbitrary hazard function and parameterize it with the Weibull duration model. The resulting Phillips curve involves lagged inflation and lagged expectations. It nests the Calvo NKPC as a limiting case in the sense that the effects of both terms are canceled out under the constant-hazard assumption. Furthermore, I find lagged inflation always has negative coefficients, thereby making it impossible to interpret inflation persistence as intrinsic. The numerical evaluation shows that the increasing hazard function leads to hump-shaped impulse responses of inflation to monetary shocks, and output leads inflation.

This paper demonstrates that tractability gained from the Calvo pricing assumption is costly in terms of aggregate dynamics. I derive a generalized New Keynesian Phillips curve featuring a generalized hazard function, non-zero steady state inflation and real rigidity. Analytically, I find that important dynamics in the NKPC are canceled out due to the restrictive Calvo assumption. I also present a general result, showing that, under certain conditions, this generalized Calvo pricing model generates the same aggregate dynamics as the gen- eralized Taylor model with heterogeneous price durations. The richer dynamic structure introduced by the non-constant hazards is also quantitatively important to the inflation dy- namics. Incorporation of real rigidity and trend inflation strengthen this effect even further. With reasonable parameter values, the model accounts for hump-shaped impulse responses of inflation to the monetary shock, and the real effects of monetary shocks are 2-3 times higher than those in the Calvo model.

This paper uses the Bayesian approach to solve and estimate a New Keynesian model augmented by a generalized Phillips curve, in which the shape of the price reset hazards can be identi…ed using aggregate data. My empirical result shows that a constant hazard function is easily rejected by the data. The empirical hazard function for post-1983 periods in the U.S. is consistent with micro evidence obtained using data from similar periods. The hazard for pre-1983 periods, however, exhibits a remarkable increasing pattern, implying that pricing decisions are characterized by both time- and state-dependent aspects. Additionally, real rigidity plays an important role, but not as big a role as found in empirical studies using limited information methods.

This paper explores implications of nominal rigidity characterized by a non-constant hazard function for aggregate dynamics. I derive the NKPC under an arbitrary hazard function and parameterize it with the Weibull duration model. The resulting Phillips curve involves lagged inflation and lagged expectations. It nests the Calvo NKPC as a limiting case in the sense that the effects of both terms are canceled out under the constant-hazard assumption. Furthermore, I find lagged inflation always has negative coefficients, thereby making it impossible to interpret inflation persistence as intrinsic. The numerical evaluation shows that the increasing hazard function leads to hump-shaped impulse responses of in‡ation to monetary shocks, and output leads inflation.

This paper demonstrates that tractability gained from the Calvo pricing assumption is costly in terms of aggregate dynamics. I derive a generalized New Keynesian Phillips curve featuring a generalized hazard function, non-zero steady state inflation and real rigidity. Analytically, I find that important dynamics in the NKPC are canceled out due to the restrictive Calvo assumption. I also present a general result, showing that, under certain conditions, this generalized Calvo pricing model generates the same aggregate dynamics as the gen- eralized Taylor model with heterogeneous price durations. The richer dynamic structure introduced by the non-constant hazards is also quantitatively important to the inflation dy- namics. Incorporation of real rigidity and trend inflation strengthen this effect even further. With reasonable parameter values, the model accounts for hump-shaped impulse responses of inflation to the monetary shock, and the real effects of monetary shocks are 2-3 times higher than those in the Calvo model.

This paper uses the Bayesian approach to solve and estimate a New Keynesian model augmented by a generalized Phillips curve, in which the shape of the price reset hazards can be identi…ed using aggregate data. My empirical result shows that a constant hazard function is easily rejected by the data. The empirical hazard function for post-1983 periods in the U.S. is consistent with micro evidence obtained using data from similar periods. The hazard for pre-1983 periods, however, exhibits a remarkable increasing pattern, implying that pricing decisions are characterized by both time- and state-dependent aspects. Additionally, real rigidity plays an important role, but not as big a role as found in empirical studies using limited information methods.

This paper explores implications of nominal rigidity characterized by a non-constant hazard function for aggregate dynamics. I derive the NKPC under an arbitrary hazard function and parameterize it with the Weibull duration model. The resulting Phillips curve involves lagged inflation and lagged expectations. It nests the Calvo NKPC as a limiting case in the sense that the effects of both terms are canceled out under the constant-hazard assumption. Furthermore, I find lagged inflation always has negative coefficients, thereby making it impossible to interpret inflation persistence as intrinsic. The numerical evaluation shows that the increasing hazard function leads to hump-shaped impulse responses of in‡ation to monetary shocks, and output leads inflation.