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This paper investigates the estimation of a linear regression model with a possible structural break at a known point. We analytically derive the exact formulae of the MSE for the restricted SR and PSR estimators, which shrinks the OLS estimator toward the restriction of no structural break. We compare the MSE performance of restricted/unrestricted SR, PSR, and least squared estimators. We analytically show that the unrestricted SR estimator can have a smaller MSE than the restricted SR estimator even when the restriction is correct. Further, our numerical results show that the unrestricted PSR estimator has the best MSE performance over a wide region of parameter space. These results indicate that the use of the unrestricted PSR estimator is recommended even when a structural break may not exist, although the unrestricted PSR estimator does not take the possibility of no structural break into consideration. [ABSTRACT FROM AUTHOR]

This article considers predictive regressions in which a structural break is allowed on an unknown date. We establish novel testing procedures for asset return predictability using empirical likelihood (EL) methods based on weighted score equations. The theoretical results are useful in practice because our unified framework does not require distinguishing whether the predictor variables are stationary or non-stationary. Monte Carlo simulation studies show that the EL-based tests perform well in terms of size and power in finite samples. Finally, as an empirical analysis, we test the predictability of the monthly S&P 500 value-weighted log excess return using various predictor variables. [ABSTRACT FROM AUTHOR]

In this article, to model risk contagion between the U.S. and China stock markets based on high-frequency financial data, we develop a novel continuous-time jump-diffusion process. For example, we consider three channels for volatility contagion—such as integrated volatility, positive jump variation, and negative jump variation—and each stock market is able to affect the other stock market as an overnight risk factor. We develop a quasi-maximum likelihood estimator for model parameters and establish its asymptotic properties. Furthermore, to identify contagion channels and test the existence of a structural break with a known structural break date, we propose hypothesis test procedures. Using the proposed diffusion model with high-frequency financial data, we investigate the effect of the U.S.–China trade war on stock markets from a financial contagion perspective. From the empirical study, we find evidence of financial contagion from the United States to China and evidence that the risk contagion channel has changed from integrated volatility to negative jump variation. [ABSTRACT FROM AUTHOR]

Testing for structural break in predictive regressions is important for empirical finance. In this article, we contribute to the literature by exploring asymptotic and finite-sample properties of three tests built upon IVX estimator proposed by Kostakis, Magdalinos and Stamatogiannis. Although they are shown to be non-pivotal, simulation studies suggest that limit distributions are highly insensitive to the variation of nuisance parameters. Furthermore, satisfactory small-sample size control and power performance can be achieved by applying critical values already tabulated in the literature. These tests are therefore easy to implement for practitioners and can serve as handy complements to other more sophisticated approaches. An empirical application concerning the break in the predictability of US stock returns is provided as an illustration. [ABSTRACT FROM AUTHOR]

Growth in agricultural total factor productivity (TFP), which explains most of the long‐term growth in U.S. agricultural output, may be slowing. The Economic Research Service (ERS) of the USDA is confident that current levels of below‐average growth will eventually regain the long‐term trend line. Others disagree, arguing instead that due to declining public expenditures on agricultural research, TFP growth experienced a downward and seemingly permanent structural shift about 30 years ago. In this paper, I argue that neither perspective is accurate since agricultural TFP is best modeled as a random walk with drift and thus not governed by a deterministic trend line. When I use a first difference model to accommodate the unit root, I do not find a structural break in the rate of drift. However, I acknowledge that this finding may not be general because I show that my test for a structural break has low power. To add theoretical relevance, I develop a simple model of stochastic innovation and farm technology adoption, and then use simulation results from my model to explain why a random walk for agricultural TFP is a theoretically sound proposition. [ABSTRACT FROM AUTHOR]

A strong surge in fertilizer prices in 2021 led farmers and policymakers to question the factors that drive fertilizer pricing. This study examines the relationship among natural gas, corn, and fertilizer prices, finding five structural breaks from 1997 to 2022. The pass‐through rates of natural gas and corn price changes to fertilizer prices show significant shifts after the passage of the biofuel mandate, with those changes fading as the market matured. Meanwhile, natural gas price changes are the main contributing factor in the latest period. However, the linkage among these prices continues to evolve and is likely to diminish over time. [ABSTRACT FROM AUTHOR]

Copyright of Ekonomik Yaklaşim is the property of Ekonomik Yaklasim Dernegi (Ekonomik Yaklasim Association) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper explores a joint test of predictability and one-time structural break, both of which are assumed to be absent under the null hypothesis. The test combines IVX estimator with a sup-Wald-type statistic. The limiting distribution of the test statistic is expected to be non-pivotal under (near-)integration. Nevertheless, for univariate cases, the distribution is highly insensitive to the variation of unestimable nuisance parameter. We hence propose to use critical values from the pivotal distribution derived under stationarity for empirical study. Simulation results suggest that this approach delivers satisfactory and robust inference in finite sample. An empirical application to the predictability of US stock returns is provided. [ABSTRACT FROM AUTHOR]

This study makes an attempt to examine the exchange rate pass-through (ERPT) to domestic prices in India from 1993M4 to 2021M3. In the empirical literature, the relationship between the exchange rate and the price was found to be linear. However, in emerging economies recently the asymmetric relationship between these variables is noticed: the effect of appreciation on price is found to be negligible while the effect of depreciation is found to be significant. To study this behaviour, we have used non-linear autoregressive distributed lag (NARDL) model by employing five variables (viz., exchange rate, consumer price, output gap, money supply and oil prices). The structural break techniques are used to examine the differential effects of the pass-through. It found that exchange rate shocks do not lead to significant changes in consumer prices in the long run. In terms of policy, this means that the ERPT has insignificant consequences for monetary policy, and depreciation might pose a little threat to price stability. It is also established that oil price shocks are not one of the major determinants of inflation in the country and they do not pose serious challenges to price stability. Economic growth and monetary expansion also do not seem to pose any risks to price stability in the long run. JEL Classification: E31, E37, E52, F31 [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic crisis was responsible for disruptions in most industries worldwide, being the wine industry a good example of how changes in the economic and social environment impacted firm performance. This research investigates whether such impacts represent a structural change to firms' profitability and explore the internal sources of such change. We consider firm-level data from Portuguese wineries, from 2014 to 2020 and apply a series of structural break tests to the period. The results allow us to conclude that the entire profitability function suffered significant changes, being COVID-19 indeed a game-breaker for wineries' profitability. [ABSTRACT FROM AUTHOR]

This paper analyses the economic confidence indicators' reaction to the environment surrounding the COVID‐19 pandemic. Using Eurostat's monthly data for the economic sentiment in European Union countries, we found that, in the COVID‐19 era, confidence and perceptions about the economy are strongly dominated by factors related to the pandemic, more so by policy measures and the vaccination process than by the direct health impact of the coronavirus. This is found to be prevalent across the multiple dimensions of economic sentiment. Moreover, standard macroeconomic variables seem to play a smaller and more marginal role during this period. [ABSTRACT FROM AUTHOR]

Long memory in test statistics can either originate from fractional integration or be spuriously induced by a short memory process with a structural break. This research estimated and detected long memory from the two causes by simulations and empirical analysis. The simulation results showed that fractional integration and structural break processes could demonstrate long memory properties. The 2ELW estimator was stable for fractional integration but not stable for time series with structural breaks. The modified W statistic based on 2ELW was efficient in discriminating fractional integration and structural breaks. Moreover, we found that six volatility time series of stock indexes and individual stocks in the Chinese market experience significant long memory and structural breaks, and the fractional differencing parameter is overestimated without controlling structural breaks.

The Central Bank of Turkey’s policy to decrease the nominal interest rate has caused episodes of severe fluctuations in Turkish lira exchange rates during 2022. According to these conditions, the daily return of the USD/TRY have attracted the risk-taker investors’ attention. Therefore, the uncertainty about the rates has pushed algorithmic traders toward finding the best forecasting model. While there is a growing tendency to employ sophisticated models to forecast financial time series, in most cases, simple models can provide more precise forecasts. To examine that claim, present study has utilized several models to predict daily exchange rates for a short horizon. Interestingly, the simple exponential smoothing model outperformed all other alternatives. Besides, in contrast to the initial inferences, the time series neither had structural break nor exhibited signs of the ARCH and leverage effects. Despite that behavior, there was undeniable evidence of a long-memory trend. That means the series tends to keep a movement, at least for a short period. Finally, the study concluded the simple models provide better forecasts for exchange rates than the complicated approaches.

Many authors state that climate change is driven by increasing CO2 emissions worldwide. An understanding of the major driving forces affecting emissions over time in both developed and developing countries is important. Thus, in this study, structural break analysis is used to identify when the trends of environmental indicators—CO2 emissions and environmental efficiency (EE)—across countries worldwide change. Our findings revealed notable structural breaks occurring in countries in 1994, coinciding with ballooning fossil energy prices. Regarding CO2, 55 of 143 countries experienced a structural break. Furthermore, another wave of structural breaks emerged in 2014, corresponding to the implementation of CO2 emission reduction plans by certain nations. For CO2, 64 of 143 countries experienced a structural break. Upon detecting breakpoints and their trends, we utilized LMDI factor decomposition analysis to discern their driving factors, thereby elucidating the underlying dynamics. In Latin America and the Caribbean, most breakpoints were undesirable shifts, but recently, desirable shifts have increased in North America, Oceania, and Europe, which include many countries with high economic levels, improving energy-related factors. Sub-Saharan Africa can also be said to have undergone an undesirable shift regarding energy-related factors. This study clarifies the precise influences on the trend of CO2 emissions at the global level by identifying the point in time when there is a significant statistical, rather than a subjective, breakpoint. [ABSTRACT FROM AUTHOR]

This study aims to investigate the stability structure of financial dollarization shocks in Türkiye. In this context, the stability structure of deposit and loan dollarization series for the period December 2005-July 2023 is tested with the conventional Augmented Dickey and Fuller (ADF), Zivot and Andrews (1992) and Lee and Strazicich (2003, 2004) unit root tests with structural breaks and Fourier ADF (2010) and Fourier Kruse (2019) unit root tests based on Fourier functions. According to the unit root test findings, deposit and loan dollarization series are found to be unit rooted at the level. This proves that financial dollarization shocks were persistent in Türkiye in the relevant period and that the Turkish economy is a dollarized economy. It is recommended that policies that can reduce the dollarization rate should be produced in order to establish permanent economic growth, financial stability and confidence in the national currency in the country. As a result, in this study, the stability structure of dollarization shocks has been investigated by using recent unit root tests. [ABSTRACT FROM AUTHOR]

This study examines the long memory properties in the volatility of the foreign exchange markets of Egypt, Ghana, Kenya, Nigeria and South Africa. Applying the FIEGARCH model to daily data from June 2, 1997, to December 31, 2021, we find long memory in the second moment of return innovations across all five countries' foreign exchange markets and significant first-order positive autocorrelation. To isolate spurious long memory, we perform a structural break test and find that structural breaks in all five foreign exchange markets do not affect long memory. The findings may have implications for risk management. Historical volatility-based investment methods can generate risk-adjusted returns innovations. Long memory may indicate unexploited profit for risk-seeking speculators and international investors in these countries' financial assets. Also, official intervention should be random and rule-changing to reduce currency market predictability. [ABSTRACT FROM AUTHOR]

Due to the structural breaks in time series, estimated current trend of product sales differs between the case where data for the entire span are used and the case where only the most recent data are used. The purpose of this study is to establish the piecewise linear approximation (PLA) as a trend analysis method that accounts for the structural breaks. PLA uses the complete data to simultaneously estimate the breakpoints and the continuously connected trends, immediately before and after the break. Thus, PLA not only ensures the ease of interpretation of the results, but also eliminates the probability of using discretion by uniquely determining the current trend, making the estimated result reliable. The case study demonstrates the proposition that, several products' sales trends and the necessity of determining an appropriate time span for data analysis, underwent changes at least once. The method's validity is demonstrated by showing the changes of the sales trends immediately after analyzed store's renovation. Data collection from the time period immediately prior to a structural break can help identify the factors changing the product sales. [ABSTRACT FROM AUTHOR]

Focusing on the Russia–Ukraine war, this paper investigates natural gas futures volatilities. Applying several hybrid GARCH and EGARCH models, which innovatively incorporate both fat-tailed distribution errors and structural breaks, we derive the following new evidence. First, our hybrid modeling approach is effective in timely capturing the natural gas futures volatility spike when tensions simmered on the Russia–Ukraine border. Second, the hybrid modeling approach is effective for not only GARCH modeling but also EGARCH modeling. Third, the volatility estimates from our hybrid models have predictive power for the volatilities of nonhybrid models. Fourth, the volatility estimates from the nonhybrid models lag behind the volatilities of our hybrid models. [ABSTRACT FROM AUTHOR]

Despite innumerable government policies to reduce youth unemployment in Sub-Saharan Africa, the problem persists. This study examines the extent to which the hysteresis effect exists in the youth unemployment rate in Sub-Saharan African countries during the period 1991 to 2021, disaggregated according to territorial delineation, income, and gender. First, we employ the univariate and panel unit root tests including the Augmented-Dickey-Fuller, Phillips-Perron, the Dickey-FullerGeneralized Least Square by Elliott, Rothenberg, and Stock (1996), the ADFmax by Leybourne (1995), and the Kwiatkowski, et al. (1992) test, to enable comparison with previous studies. The Pesaran's (2007), test is then applied to account for cross-sectional dependence. Finally, the Zivot– Andrews single structural break by Zivot and Andrews (1992), Clemente–Montane–Reyes two structural breaks unit root tests by Clemente, Montañés, and Reyes (1998), as well as the KaraviasTzavalis panel unit root test with structural breaks by Karavias and Tzavalis (2014) are employed. The univariate unit root tests generally support the hysteresis hypothesis (within a band of 60% to 97%) for almost all countries, and sub-regions in SSA. However, accounting for structural breaks, the hysteresis effect in total youth unemployment is only visible in 19 countries (40%), with evidence of gender disparities pointing to the hysteresis effect in females only in 16 countries (34%), and, in males only in 10 countries (21.3%). The lower-middle-income countries reject the natural rate hypothesis in total and both male and female youth unemployment rates. While only male youths suffer from the hysteresis in low-income countries, the total youth in upper-middle-income countries shares this effect. Accounting for cross-section dependence alters the finding of the hysteresis effect only in males in Southern Africa and upper-middle-income countries. A one-size-fits-all policy may not work. Instead, we recommend an integral approach aimed at the creation of employment opportunities for youth and females, including but not limited to diversification of economic activities in rural areas to reduce urbanization, skills training, political and economic stability, cultural transformation to remove unnecessary gender-related employment discrimination, as well as improved economic integration policies. For countries found to exhibit the natural rate hypothesis, it may not be necessary to engage in costly policies to return the youth unemployment rate to equilibrium since the shock is only temporary. [ABSTRACT FROM AUTHOR]

This paper proposes a frequentist model averaging approach in the presence of parameter instability and heteroskedasticity. We derive optimal weights combining the stable and break specifications of a predictive model, with the weights from minimizing the leave‐one‐out cross‐validation information criterion (CV). We characterize the asymptotic distribution of the CV and provide the analytical expressions of the feasible optimal CV weights. Our simulations and applications forecasting the US and Taiwanese GDP growth demonstrate the superior performance of the CV model averaging relative to other methods such as the Mallows averaging, the approximate Bayesian averaging, and equal weighting. [ABSTRACT FROM AUTHOR]

Cryptocurrencies have emerged as an important investment avenue in the past few years. Investors are increasingly interested in these currencies amid surging financial returns. In this context, understanding market efficiency of cryptocurrency has become very crucial for investors and academicians. The price–volume framework is a popular approach in financial economics to understand the market efficiency of stocks in the stock markets. Therefore, this article examines the market efficiency of cryptocurrencies through price–volume framework to understand whether crypto market is predictable. Towards this objective, data on both return and trading volume (TV) of the top eight cryptocurrencies are used for the period 8 August 2015–20 October 2022. As an empirical method, both linear and non‐linear causality models are used to validate the hypothesis. Our results confirm that TV cannot predict the cryptocurrencies' return, thereby validating the market efficiency hypothesis. Furthermore, we divide the sample according to the structural break period. The result from the post‐break period analysis also confirms the presence of market efficiency in the recent period for all currencies, barring XRP, XMR and DASH. [ABSTRACT FROM AUTHOR]

This paper suggests a new testing procedure to systematically examine the middle-income trap (MIT). To empirically demonstrate this procedure, one high income and 14 middle-income countries are examined using newly developed unit root tests — Fourier ADF with structural break (FADF-SB) and Seemingly Unrelated Regressions Fourier ADF (SUR-FADF). The FADF-SB test incorporates unknown nonlinearity and smooth break in the time-series, while the SUR-FADF test accounts for cross-sectional dependency. The empirical findings produced mixed results: 10 countries have a relatively high possibility of facing the MIT problem, while only one country has a relatively low possibility of facing the problem. For the remaining three countries, it is uncertain whether they will face the problem of MIT. These empirical findings have significant policy implications. [ABSTRACT FROM AUTHOR]

The introduction of Bitcoin as a distributed peer-to-peer digital cash in 2008 and its first recorded real transaction in 2010 served the function of a medium of exchange, transforming the financial landscape by offering a decentralized, peer-to-peer alternative to conventional monetary systems. This study investigates the intricate relationship between cryptocurrencies and monetary policy, with a particular focus on their long-term volatility dynamics. We enhance the GARCH-MIDAS (Mixed Data Sampling) through the adoption of the SB-GARCH-MIDAS (Structural Break Mixed Data Sampling) to analyze the daily returns of three prominent cryptocurrencies (Bitcoin, Binance Coin, and XRP) alongside monthly monetary policy data from the USA and South Africa with respect to potential presence of a structural break in the monetary policy, which provided us with two GARCH-MIDAS models. As of 30 June 2022, the most recent data observation for all samples are noted, although it is essential to acknowledge that the data sample time range varies due to differences in cryptocurrency data accessibility. Our research incorporates model confidence set (MCS) procedures and assesses model performance using various metrics, including AIC, BIC, MSE, and QLIKE, supplemented by comprehensive residual diagnostics. Notably, our analysis reveals that the SB-GARCH-MIDAS model outperforms others in forecasting cryptocurrency volatility. Furthermore, we uncover that, in contrast to their younger counterparts, the long-term volatility of older cryptocurrencies is sensitive to structural breaks in exogenous variables. Our study sheds light on the diversification within the cryptocurrency space, shaped by technological characteristics and temporal considerations, and provides practical insights, emphasizing the importance of incorporating monetary policy in assessing cryptocurrency volatility. The implications of our study extend to portfolio management with dynamic consideration, offering valuable insights for investors and decision-makers, which underscores the significance of considering both cryptocurrency types and the economic context of host countries. [ABSTRACT FROM AUTHOR]

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The aim of this article is to provide an explanation of French (dis)inflation based on the conflictingclaims theory. Making use of cointegration techniques with structural breaks, we bring some empirical evidence suggesting the soundness of such a theory in order to explain the variation of inflation in the long run. Amongst our main results, we show that the transition from the Great Inflation of the 1970s to the Great Moderation was the consequence of a dramatic collapse in the bargaining power of both workers and firms. As a secondary objective, it is also an attempt to fill the gap with other competing theories of inflation since the conflicting-claims approach is characterized by a relative paucity in terms of empirical works. [ABSTRACT FROM AUTHOR]

In this manuscript we introduce a mixture integer-valued autoregressive model with a structural break. The introduced model is a mixture of an INAR(1) model with the binomial thinning operator and an INAR(1) model with the negative binomial thinning operator. Some properties of the introduced model are derived. The unknown parameters of the model are estimated by some methods and the performances of the obtained estimators are checked by simulations. At the end of the paper, two possible applications of the model are provided and discussed. [ABSTRACT FROM AUTHOR]

Copyright of Omer Halisdemir Universitesi Iktisadi ve Idari Bilimler Fakültesi Dergisi is the property of Omer Halisdemir University, Faculty of Economics & Admistrative Sciene and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Introduction: Islamic stock is believed to be more stable and less risky than conventional stock due to specific screening based on Sharia principles, particularly during economic downturns. This research aims to investigate whether the Covid-19 outbreak caused a structural break in Indonesia's Islamic and conventional stock markets. Methods: This study covers the period from January 2007 to June 2022, divided into sub-periods before Covid-19 (January 2007 to February 2020) and during COVID-19 (March 2020 to June 2022). The study adopts the time series regression method to examine the predicting factors of Islamic and conventional stock indexes, followed by the application of the Chow Breakpoint Test method to determine whether there are structural changes in the Islamic and conventional stock markets due to Covid-19. Results: The results of this study suggest that, in comparison to the period preceding Covid-19, the Islamic stock index demonstrates heightened sensitivity to fluctuations in predicting factors during the pandemic. Additionally, there is an absence of any structural break observed in conventional indices. Consequently, Islamic stocks exhibit lower resistance during crisis periods than conventional stocks. Conclusion and suggestion: This finding prompts a comprehensive evaluation of the Sharia screening standards by policymakers to enhance the resilience of Islamic stocks during economic turmoil. Moreover, based on the results, it is suggested that investors cannot consider the Islamic stock index as a 'safe-haven' instrument during financial turmoil. The result of this research assist investors in adjusting their investment strategies more effectively, particularly in bearish market conditions. [ABSTRACT FROM AUTHOR]

We look into the weak-form informational efficiency for twelve sectors in Malaysia's stock exchange, i.e. Consumer Products & Services (KLCSU), Construction (KLCON), Energy (KLENG), Financial Services (KLFIN), Health Care (KLHEAL), Industrial Products & Services (KLPRO), Property (KLPRP), Plantation (KLPLN), Transportation & Logistics (KLTRAN), Telecommunications & Media (KLTEL), Utilities (KLUTL), and Technology (KLTEC) during the outbreak of COVID-19 pandemic. We use QTEST (without trend) and TQTEST (with trend), which incorporate two structural breaks to carry out the analysis. Data are collected from 02/12/2019 through 31/3/2022. These indices show non-linearity and structural breaks in data. The findings of our study suggest mixed results regarding informational efficiency when breaks are taken. Four indices, i.e. KLCON, KLFIN, KLPRP, and KLUTL, are found to be inefficient, while the remaining eight sectors are found to be efficient. [ABSTRACT FROM AUTHOR]

The aim of this study is to analyze bifurcation points in financial models using colored noise as a stochastic component. The research investigates the impact of colored noise on change-points and approach to their detection via neural networks. The paper presents a literature review on the use of colored noise in complex systems. The Vasicek stochastic model of interest rates is the object of the research. The research methodology involves approximating numerical solutions of the model using the Euler–Maruyama method, calibrating model parameters, and adjusting the integration step. Methods for detecting bifurcation points and their application to the data are discussed. The study results include the outcomes of an LSTM model trained to detect change-points for models with different types of noise. Results are provided for comparison with various change-point windows and forecast step sizes. [ABSTRACT FROM AUTHOR]

In this study, the structure of price variability is analyzed over the inflation rates of selected countries in the Eurozone using monthly data between 2001M1-2022M11. The structure analysis is analyzed by estimating a process by which inflation rates move from stationary to non-stationary or vice versa across different periods. In addition, in this analysis, forecasts were also made to determine the change points of inflation rates for all countries analyzed. Our findings suggest that the tendency for inflation rates to revert to the mean continued before the covid19 period. This can be interpreted as a persistence and resistance to the 2% inflation rate envisaged for price stability and inflation targeting. However, according to our analysis results, there is a change in the structure of the tendency of the inflation rate to return to the average during the covid19 pandemic period. [ABSTRACT FROM AUTHOR]

We develop methods to obtain optimal forecast under long memory in the presence of a discrete structural break based on different weighting schemes for the observations. We observe significant changes in the forecasts when long-range dependence is taken into account. Using Monte Carlo simulations, we confirm that our methods substantially improve the forecasting performance under long memory. We further present an empirical application to inflation rates that emphasizes the importance of our methods. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Finance Letters / Maliye Finans Yazıları Dergisi is the property of Maliye Finans Yazilari Yayimcilik Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

AbstractThis paper investigates the consistency of asymmetric interest rate past-trough (IRPT) using a nonlinear autoregressive distributed lag framework. Superior to the previous studies, this study exploits the historical profile of Indonesia to enrich the analysis. Asian Financial Crisis (AFC) which crashed the country in 1998 and several monetary policy changes implemented by the government offer different perspectives to grasp IRPT. The results of this study indicate that there is a consistent upward rigidity in the long-run pass-through in Indonesia. Particularly during the AFC, it is well proven that the asymmetric behavior is fickle whether disappear or bounce back to the downward rigidity. This finding demonstrates the importance of a rolling-window approach in understanding IRPT.

In this study, we estimate and investigate the evolution of monetary rules in China and the United States in the 21st century. Our goal is to examine whether financial stability has been taken into consideration in the decision-making of monetary policy. By proposing a new method, we estimate the structural breaks, split the entire time period into multiple monetary regimes, and estimate an extended Taylor rule with financial stability considerations and its evolution over time. Our findings show that China's monetary policy emphasized the financial stress of the U.S. immediately before and during the 2008 global financial crisis. However, the coefficient for the U.S. financial stress has decreased since then, which shows a weaker concern on this index, and instead, the Chinese policymakers are emphasizing stronger on their domestic financial market. [ABSTRACT FROM AUTHOR]

We explore the possibilities and limitations of models of the demand for military expenditures, as against additional kinds of cross-country analyses, with an empirical focus on the Indo-Pacific region. Our research bridges a gap between the Defence Economics and International Relations literatures by developing testable security alignment hypotheses and by testing these hypotheses in three ways: with demand modelling on total expenditures, with analyses on estimated stocks of imported armaments, and with qualitative analyses of trends in defence cooperation between states. We find consistent evidence across research methods of an increase in threat perceptions towards China since around 2012 and of balancing behaviour by US allies and by two non-allies. As compared to standard demand modelling, our hypothesis-based mixed methods approach allows for a clearer treatment of samples with mixed and shifting security alignments and of states that stabilise or reduce expenditures in the face of rising threat perceptions. [ABSTRACT FROM AUTHOR]