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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.

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.

The purpose of this study is to investigate and evaluate the impact of the global Covid-19 crisis on consumer spending tendencies in Turkey. The data of the study, which are weekly data, consists of the "Debit Card and Credit Card Expenditure" amounts of the Central Bank of the Republic of Turkey (CBRT) for the period 6/3/2015–5/8/2022. Changes in consumer expenditures during the Covid-19 pandemic process were examined with the help of structural break tests. The main contribution of this article subsists in an empirical study to examine structural breaks in Turkey using personal debit and credit card disaggregated total expenditure data during the Covid-19 period. According to the research findings; the change observed at the beginning of the Covid-19 period in card expenditures is less than the change observed at the end of the period. With the end of the pandemic, an upward breakout was observed in most of the expenditure items.

ÖZ: Bu çalışmada M. Friedman’ın vergi-harcama hipotezi Türkiye (2006-2022) örneği üzerinden araştırılmıştır. Araştırmanın uygulaması iki aşamada gerçekleştirilmiştir. İlk olarak araştırmanın değişkenleri geleneksel birim kök testlerine (Augmented Dickey-Fuller ve Phillips-Perron testlerine) tabi tutulmuş ve ardından Engel-Granger koentegrasyon analizi yapılmıştır. İkinci aşamada değişkenler yapısal kırılmalı birim kök testlerine (Zivot-Andrews ve Lee-Strazicich testlerine) tabi tutulmuş ve yapısal kırılmayı dikkate alan Gregory-Hansen koentegrasyon analizi yapılmıştır. Sonuç olarak her iki yöntem benzer sonuçlar vermiş ve vergi-harcama hipotezinin Türkiye (2006-2022) için geçerli olduğunu sonucuna ulaşılmıştır. ABSTRACT: In this study, M. Friedman’s tax-expenditure hypothesis was investigated through the example of Turkey (2006-2022). The implementation of the research was carried out in two stages. First, the variables of the research were subjected to traditional unit root tests (Augmented Dickey-Fuller test and Phillips-Perron test) and then the Engel-Granger cointegration analysis was performed. In the second stage, the variables were subjected to unit root tests with structural break (Zivot-Andrews test and Lee-Strazicich test) and Gregory-Hansen cointegration analysis, which took into account the structural break, was performed. As a result, both methods gave similar results and it was concluded that the tax-expenditure hypothesis is valid for Turkey (2006-2022).

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.

This paper quantitatively reveals the meaning of structural breaks for risk management by analyzing US and major European banking sector stocks. Applying newly extended Glosten-Jagannathan-Runkle generalized autoregressive conditional heteroscedasticity models, we supply the following new evidence. First, we find that incorporating structural breaks is always effective in estimating banking stock volatilities. Second, we clarify that structural breaks partially explain the tail fatness of banking stock returns. Third, we find that when incorporating structural breaks, the estimated volatilities more accurately capture their downside risk, proving that structural breaks matter for risk management. Fourth, our news impact curve and model parameter analyses also uncover that when incorporating structural breaks, the asymmetry in volatility responses to return shocks is more accurately captured. This proves why the estimated volatilities by incorporating structural breaks better explain downside risk. In addition, we further reveal that the estimated volatilities obtained through incorporating structural breaks increase sharply during momentous events such as the Lehman crisis, the European debt crisis, Brexit, and the recent COVID-19 crisis. Moreover, we also clarify that the volatility spreads between models with and without structural breaks rise during the Lehman and COVID-19 crises. Finally, based on our findings, we derive many significant and beneficial interpretations, implications, and innovative views for risk management using artificial intelligence in the post-COVID-19 era.

This paper examines the effects of volatility spillover between MIST stock markets. We used daily data from January 3, 2012, to November 16, 2021, and the test of causality in variance, including structural breaks. First, we observed no structural break for Turkey and Indonesia, but there is a structural break in each South Korean and Mexican stock markets. A structural break is found for Mexico the day, aka "El Betito" was arrested. Likewise, we detected a structural break on the first day of the Covid-19 case for South Korea. We surprisingly observed that Covid-19 did not cause a structural break in these markets during the period analyzed, except in South Korea. GARCH (1, 1) models, including structural breaks, show that all series are temporarily and permanently affected by their own shocks. The causality in variance test reveals that MIST countries have volatility spillover effects on each other. There is bidirectional causality in variance between all markets, except South Korea and Mexico. The Mexican stock market is a volatility transmitter for South Korea, but vice versa. The paper indicates a connection in terms of the financial markets of MIST countries, and they are affected by each other's shocks, according to the study results.

We analyze the behavior of inflation in the era of fast pace information thanks to technological advances, especially internet. Owing to readily available information, prices/inflation should quickly converge under perfect competition. To this end, we explore the possibility of price convergence in regional inflation in the USA including the permanency of such a phenomenon if observed, a concern for monetary policy makers. Empirically, we analyze standard deviation of regional inflation with special attention to technology. We show that standard deviation of inflation is not constant over time, but not necessarily ever-declining. Technology seems to help reduce price dispersion across regions. First published online 12 October 2021

2019 yılının Aralık ayında Çin’in Wuhan şehrinde ortaya çıkan Covid-19 virüsü 2020 yılı ile küresel bir salgına dönüşmüştür. Küresel salgından birçok ülke ekonomisi olumsuz etkilenmiştir. Buna ek olarak, salgının dış ticaret üzerinde de olumsuz etkisi olmuştur. Bu çalışmanın amacı Türkiye’nin ekonomik büyümesinde büyük itici gücü olan dış ticaretin, salgından nasıl etkilendiğinin analiz edilerek literatüre katkı sağlamaktır. Çalışmada Türkiye’nin 2013:01 ile 2020:11 dönemi ihracat ve ithalat verileri kullanılmıştır. Çalışmanın analizi iki bölümden oluşmaktadır. İlk olarak Bai ve Perron yapısal kırılma testi ile değişkenlerin kırılma tarihleri belirlenmiştir. İkinci olarak ise, bu kırılma tarihleri dikkate alınarak iki değişken için; trendde yapısal değişiklikler analizi yapılmıştır. Sonuç olarak; ihracat ve ithalat için 2020:2 tarihinde kırılma olduğu tespit edilmiştir. Yapısal değişiklik analizlerinde ise; salgının Türkiye’nin ihracat ve ithalat eğrilerinin eğimini değiştirdiği fakat ihracat ve ithalatın kısa sürede toparlandığı görülmüştür.

Büyüme, döviz girişi, ödemeler dengesi, yatırım fırsatları ve yeni istihdam alanları üzerindeki olumlu etkisi açısından turizm, günümüzde ekonomideki en önemli sektörlerden biridir. Turizm gelirlerinin reel ekonomik büyümeye ve reel döviz kuru ile etkileşimini araştırmak da bu çalışmanın temel motivasyonudur. Bu motivasyon ile, bu çalışmada 2003Q1-2020Q1 dönemine ait çeyreklik veriler kullanılarak turizm gelirleri, reel hale getirilen ekonomik büyüme ve döviz kuru arasındaki ilişki araştırılmıştır. Bu araştırma Zivot ve Andrews yapısal kırılmalı birim kök sınaması, Johansen eş bütünleşme analizi, FMOLS ve DOLS yöntemleri ile katsayı tahminleri ve son olarak Toda-Yamamoto testi ile nedensellik analizi aracılığıyla yapılmıştır. Araştırma sonucu olarak, değişkenler arasında uzun dönemli ilişkinin olduğu, bağımlı değişken reel milli geliri açıklayan bağımsız değişkenler turizm gelirleri ve reel döviz kurunun olasılık değerlerinin anlamlı oldukları ve kat sayı işaretlerinin pozitif oldukları görülmüştür. Reel döviz kurunun reel milli geliri etkile gücü turizm gelirlerine nispeten daha fazladır. Yapısal kırılma tarihlerinden 2016Q2 ve 2017Q1 anlamlı çıkması, bu dönemdeki terör olaylarına, Rusya ile yaşanan gerilime ve darbe girişiminin tüm dünyada yankı uyandırması ile açıklanabilir. Toda-Yamamoto nedensellik analizine göre reel milli gelirden ve reel döviz kurundan turizm gelirlerine doğru pozitif ve tek yönlü bir Granger nedensellik vardır.

Following the keep-it-sophisticatedly-simple principle, KISS, we propose using the averaging window approach to forecast the market equity premium in unstable environments. First, the estimation methodology of averaging window is a theoretically justified method robust to uncertainties on structural breaks and estimation window sizes. Second, the averaging window method has the obvious advantages of being understandable to forecast users and simple to implement, thus encouraging engagement and criticism. Our empirical results demonstrate the superior performance of the averaging window when forecasting the U.S. market equity premium, exceeding a wide range of methods which have been shown effective, such as shrinkage estimators and technical indicators.

Container ports are one of the most important parts of the supply chain. Due to high investment and operating costs, the structure and predictability of current and future demands are very important. To investigate this structure, this study aims to determine whether the shocks to the export and import container quantities handled in Turkish ports are temporary or permanent. Both standard unit root tests and unit root tests with structural breaks were applied to export and import container amounts. According to the results, when the structural breaks are considered, it has been determined that both export and import container quantities are stationary. This situation shows that the effects of the shocks to the container traffic are temporary, the applied policies lose their effect in a short time and the future container traffic can be predicted using historical data.

Abstract In this study we propose a fractional frequency flexible Fourier form fractionally integrated ADF unit-root test, which combines the fractional integration and nonlinear trend as a form of the Fourier function. We provide the asymptotics of the newly proposed test and investigate its small-sample properties. Moreover, we show the best estimators for both fractional frequency and fractional difference operator for our newly proposed test. Finally, an empirical study demonstrates that not considering the structural break and fractional integration simultaneously in the testing process may lead to misleading results about the stochastic behavior of the Covid-19 pandemic.

The present paper attempts to find out the spatial and temporal movement of rice yield in twelve countries in Asia which is its lifeline over the period 1961 to 2016 by following Bai-Perron multiple structural break tests. The results based on endogenous multiple structural break analysis show that many of these countries passed through several phases of acceleration and deceleration in rice yield over this period The results also demonstrate that except Japan, all the twelve countries considered in our study experienced at least one structural break in rice yield at level during the period 1961 to 2016. The acceleration phases of rice yield growth observed mostly during 1970's and 1980's are resulted from improved technological innovations in agriculture whereas deceleration phases observed in the last two decades are mainly caused by environmental challenges on rice production. Cross country yield gaps have been showing declining trend since early 80's.

This paper assesses the stochastic convergence of relative per capita ecological footprints within BRICS countries over the period 1961–2017 in the field of Public Health. Our initiatives have targeted ecological Indicator and health behaviors. Using the local Whittle estimator and some of its variants we assess whether relative per capita ecological footprints are long memory processes which, although highly persistent, may revert to their mean/trend in the long run thereby indicating evidence of stochastic convergence, or divergent processes in nutshell. Furthermore, we test whether (possibly) slow convergence or the complete lack of it may be the result of structural changes to the deterministics of each of the relative per capita footprint series by means of the tests of Berkes et al. (1) and Mayoral (2). For the ease of comparison, this paper assesses the stochastic convergence of relative per capita ecological capacities for BRICS as well. Our results show relatively strong evidences against stochastic convergence of ecological footprints. Furthermore, with regard to China and Russia, our results also decisively indicate that a slow or lack of convergence is the results of a structural break in the relative per capita ecological footprint series. However, our empirical researches support stochastic convergence of relative per capita ecological capacities for BRICS. In addition, we can conclude whether the per capita ecological footprints converge or not is dependent on the level of economic development, and the stochastic convergence occurs in those rich countries more probably, indicating that public health is becoming a more serious concern in developing countries.

Öz: Bu çalışmada, “Kırılgan Beşli” olarak adlandırılan ülkelerde (Brezilya, Endonezya, Güney Afrika, Hindistan, Türkiye), 2009-2019 arası veriler aylık bazda kullanılarak korunmasız faiz oranı paritesinin geçerliliğinin, zaman serileri yöntemiyle eşbütünleşme ve asimetrik nedensellik modelleri oluşturularak test edilmesi amaçlanmıştır. Çalışmada, Kırılgan Beşli ülkelerde faiz oranı paritesinin geçerliliği hem yapısal kırılmalı eşbütünleşme testleri ile hem de kırılmasız eşbütünleşme testleri ile sınanmış ve elde edilen bulgulara göre, yapısal kırılmayı dikkate almayan (ADF, PP, KPSS) birim kök testleri ve Engle & Granger (EG) (1987) eşbütünleşme testi sonuçları, analize tabi tutulan tüm ülkelerde faiz oranı paritesinin geçerli olmadığını göstermiştir. Aynı testler yapısal kırılmayı dikkate alan Zivot & Andrews (ZA) (1992) yapısal kırılmalı birim kök ve Gregory & Hansen (GH) (1996) yapısal kırılmalı eşbütünleşme modelleri yardımıyla tekrarlandığında ise, analiz sonuçlarının farklılaşabileceği görülmüştür. Yapısal kırılmayı dikkate almayan modellere göre hiçbir ülkede eşbütünleşme tespit edilememişken, yapısal kırılmalı model sonuçlarına göre Brezilya’da eşbütünleşme tespit edilmiş ve faiz oranı paritesinin geçerli olduğu görülmüştür. Dolayısıyla, elde edilen bu sonuç, yapılan çalışmalarda, yapısal kırılmalı modellerin dikkate alınmasının gerekliliğini göstermiştir. Hatemi-J (2012) asimetrik nedensellik testi sonuçlarına göre, Brezilya, Endonezya, Güney Afrika ve Hindistan ülkelerinde nedensellik bulgularına ulaşılmıştır. Abstract: In this study, the validity of uncovered interest rate parity was aimed to be tested using historical data for montly basis from 2009-2019 by forming the cointegration and asymmetric causalty modelswith time series method in countries called “Fragile Five” (Brazil, Indonesia, South Africa, India, Turkey). Thevalidity of the interest rate parity in Fragile Five countries was tested with both cointegration tests with structural break and without structural break. According to the findings obtained, without structural break unit root tests and Engle&Granger (EG) (1987) cointegration test results showed that the interest rate parity was not valid in all countries analyzed. When the same tests were repeated with unit root model with structural break and Gregory&Hansen (GH) (1996) cointegration model with structural break, it was seen that analysis results could differ. According to the models that did not take into account the structural break, cointegration was not detected in any country, while the results of the models with structural break showed cointegration in Brazil and the interest rate parity was valid. Therefore, this result showed that the models with structural break should be taken into consideration in the studies. According to the results of the Hatemi-J(2012) asymmetric causality test, causality relationship findings were obtained in Brazil, Indonesia, South Africa and India.

The IMF reports that, over 60% of foreign trade income and 40% of government revenue of Iran comes from the oil and gas sectors, which has always been a source of volatilities in the economy. The imposed sanctions on the Iranian economy also influence economic activities by reducing currency earnings and restricting access to capital and intermediaries goods. Understanding extent of the shocks’ effects of sanctions and fluctuations in oil revenue, are key factors for the policymakers in foreseeable planning risks. In order to examine the effect of sanctions and oil price(revenue) fluctuations on the country's economy, this paper intends to quantify the effects of sanction by making use of a VARMAX GARCH-in-Mean Asymmetric BEKK model in terms of structural failure of the conditional variance. We use real non-oil GDP, Iranian heavy oil exports, exchange rates, total stock market index and sanctions index data over 1991:Q2 to 2018:Q1. The results show that a shock of oil revenue or sanctions index affects activities in all of three sectors. The increasing sanctions pressure leads to a spillover effect of uncertainty to all sectors under study and a decline in production activities and national currency depreciations; but in turn the relative share of the stock market in the portfolio of investors' choice increases. Strong evidence for asymmetric effects of impulses of sanction and oil revenue on the study sections is observed.

The present study examines the relationship between FDI inflows and export performance in Bangladesh by considering the issue of structural breaks utilizing annual time-series data from 1972 to 2019. In the study, unit root tests were conducted without (ADF test and PP test) and with (ZA test and LP test) the presence of probable structural breaks in the dataset. A Johansen test of co-integration was employed to determine whether the variables were co-integrated. The VECM was used for determining the sources of causation and the directions of the causal relationships between the variables. Since all the variables were integrated of order one, I(1), with breaks (confirmed by ZA and LP unit root tests), a Johansen test of co-integration was applied to identify whether the variables were co-integrated. The results of the Johansen co-integration test confirmed that three variables (LRGDPGR, LRFDI, and LREX) have a long-run equilibrium relationship or cointegrating relation. Finally, the VECM suggests the evidence of a positive and unidirectional causal relation from REX to RFDI in Bangladesh. An important uniqueness of this study lies in its application of the methodological issues of incorporating structural breaks, which could have significant implications for investigating the said relationship.

Emerging or diminishing nonlinear interactions in the evolution of a complex system may signal a possible structural change in its underlying mechanism. This type of structural break may exist in many applications, such as in climate and finance, and standard methods for change-point detection may not be sensitive to it. In this article, we present a novel scheme for detecting structural breaks through the occurrence or vanishing of nonlinear causal relationships in a complex system. A significance resampling test was developed for the null hypothesis (H0) of no nonlinear causal relationships using (a) an appropriate Gaussian instantaneous transform and vector autoregressive (VAR) process to generate the resampled multivariate time series consistent with H0; (b) the modelfree Granger causality measure of partial mutual information from mixed embedding (PMIME) to estimate all causal relationships; and (c) a characteristic of the network formed by PMIME as test statistic. The significance test was applied to sliding windows on the observed multivariate time series, and the change from rejection to no-rejection of H0, or the opposite, signaled a non-trivial change of the underlying dynamics of the observed complex system. Different network indices that capture different characteristics of the PMIME networks were used as test statistics. The test was evaluated on multiple synthetic complex and chaotic systems, as well as on linear and nonlinear stochastic systems, demonstrating that the proposed methodology is capable of detecting nonlinear causality. Furthermore, the scheme was applied to different records of financial indices regarding the global financial crisis of 2008, the two commodity crises of 2014 and 2020, the Brexit referendum of 2016, and the outbreak of COVID-19, accurately identifying the structural breaks at the identified times.

Abstract This study analyzes the relationship between savings, investment, and economic growth in Nepal over 1975–2016. The structural breaks in the variables have been accounted for using the (Zivot and Andrews’s, J Bus Econ Stat 10: 251–270 1992) unit root test along with (Gregory and Hansen’s, Oxf Bull Econ Stat 58: 555–560, 1996) cointegration approach. The ARDL approach to cointegration in the presence of structural breaks has also been utilized to analyze the long-and short-run dynamics of savings, investment, and growth in Nepal. The results show structural breaks in the real GDP per capita during 2001 when the Royal Massacre and a state of emergency have taken place in Nepal. After allowing for this structural break, evidence of a cointegration relationship amongst savings, investment, and economic growth was identified. The estimates of the ARDL approach suggest that investment has a significant and positive impact on economic growth. However, gross domestic savings have a negative impact on growth in the long run. These results clearly show weaknesses of the economy in mobilizing savings into productive sectors.

Due to the importance of limited energy resources in the world, researchers and policy makers pay more attention to energy intensity. The purpose of the paper is to study the effect of structural break on factors influencing energy intensity in Iran during the period of 1979-2013. The Fully Modified Ordinary Least Squares (FMOLS) method was used to estimate co-integrating relationships among variables under study. The results showed that energy price and foreign direct investment had negative effects, and share of industrial value added had a significant positive effect on energy intensity. Then structural break was included in the model as a dummy variable. Findings indicate that 1987’s structural break has reduced the impact of energy price and industrial value added, which points to a decrease in the price elasticity of energy intensity and an increase in productivity of the industrial sector after structural break. However, such break had no significant effect on the relationship between direct foreign investment and energy intensity.

This study aims to provide a decomposition analysis on aggregate energy intensity in Ethiopia over 1990–2017 using Logarithmic Mean Divisia Index (LMDI) I decomposition method. It also investigates the main driving forces influencing the observed energy intensity trend in the presence of a structural break. The LMDI I decomposition results indicate that the efficiency component has played a prominent role in reducing the overall energy intensity while the contribution of structural component for the change in total intensity has been very negligible. On the other hand, the model estimation results with structural break invariably confirm that economic growth, modern renewable energy, and institutional quality appear to have a significant negative effect on total energy intensity in the long run (contribute positively for energy efficiency improvement) while industrialization and FDI stock tend to induce higher energy intensity. Further, modern renewable energy negatively moderates the effect of growth and industrialization on energy intensity. After all, the results suggest the need for giving a strong emphasis for sector-specific energy efficiency which may have an important implication not only on economic growth but also on environmental sustainability. Policy measures promoting clean energy transformation and better institutional setup also need to be highly encouraged.

This study utilizes a bivariate BEKK-EGARCH model with the setting of a structural break to investigate whether the interactions between stock indices in emerging and developed markets are different in terms of region, emerging stock indices, and subperiod. Then, this study investigated how the results of interactions vary with geographical location, emerging stock indices, and subperiod. Empirical results show that the interactions between emerging and developed markets indeed vary with geographical location and emerging stock indices, but are almost the same in the two subperiods. For example, for the paired stock indices in ‘Asia-America’ and ‘Asia-Europe’, or related to ‘XU100’, ‘SSE’ and ‘BSE’, the developed market mainly spills into the emerging market in terms of return and volatility. The findings from these empirical results can help investors and fund managers undertake different investment strategies in different regions and subperiods, and make effective investments.

Millets are the major substitute for cereals such as rice and wheat. For developing country like India, millets hold immense importance as the cost of production is low and has high nutritional values. Various policy interventions are made by government of India from time to time to popularise its consumption and production. Few major policy interventions were made in last decade and inclusion of coarse cereals under Food Security Bill is one among them. Keeping this in mind, the present study was carried out at ICAR- Indian Agricultural Statistics Research Institute, New Delhi during 2018 to know the impact of policy interventions on the price index of Ragi. Further, we have introduced these interventions in the model using structural break analysis. The volatile Ragi price index series were modelled and forecasted using popular class of Generalised Autoregressive Conditional Heteroscedastic (GARCH) models and its asymmetric extensions. The results indicated improvement in modelling and forecasting performance of the models after incorporation of the policy interventions. Study has empirically highlighted the positive impact of policies introduced.

This paper studies the dynamic behaviour of both linear and non-linearity of consumer prices in Peninsular Malaysia and Sabah from 2004 to 2015. For linear tests, monthly prices data of consumer price index (CPI) for nine groups of goods and services were analysed using the unit root tests and cointegration tests with structural breaks; while for non-linear test, NARDL test is incorporated. The findings indicated that (i) both Zivot and Andrews unit root test and Perron unit root test provided fairly similar results; most of the breakpoints occurred in 2008, followed by 2012 and 2013, (ii) the variables did not cointegrate in the Johansen cointegration test which indicates that no stable long-run relationship was reflected in the CPI for all groups, except for “transport”, and (iii) the Gregory and Hansen test demonstrated some form of cointegration with a structural break(s) existed, with a most recorded break in 2008 (iv) the NARDL test shows a fair impact of asymmetrical interaction for all groups except for Housing, Water, Electricity, Gas, and Other Fuels; Health and Recreation Services and Culture. Overall, this study intends to match the structural break points and the groups affected with the corresponding critical economic incidents.

Economics suffers from a blurred view of the economy due to the delay in the official publication of macroeconomic variables and, essentially, of the most important variable of real GDP. Therefore, this paper aimed at nowcasting GDP in India based on high-frequency data released early. Instead of using a large set of data thus increasing statistical complexity, two main indicators of the Indian economy (economic policy uncertainty and consumer price index) were relied on. The paper followed the MIDAS–Almon (PDL) weighting approach, which allowed us to successfully capture structural breaks and predict Indian GDP for the second quarter of 2021, after evaluating the accuracy of the nowcasting and out-of-sample prediction. Our results indicated low values of the RMSE in the sample and when predicting the out-of-sample1- and 4-quarter horizon, but RMSE increased when predicting the 10-quarter horizon. Due to the effect of the short-term structural break, we found that RMSE values decreased for the last prediction point.

This study investigates the relationship between labour productivity, average real wages, and the unemployment rate by employing the bounds testing procedure within an autoregressive distributed lag (ARDL) modeling approach and applies Toda-Yamamoto causality test for the period 2007:01−2016:04. The results indicate that real wages and unemployment have a significant and positive long-run impact on labour productivity. While a long-run wage–productivity elasticity of 0.97 supports the efficiency wage theorem and the unemployment-productivity elasticity of 0.53 indicates that workers increase efforts to secure jobs. Therefore, a rise in real wages and unemployment may induce higher productivity by raising the costs and probability of job loss, respectively, which implies rigidity in Turkish labour market.Furthermore, the causality tests provide evidence for the effect of a high and persistent unemployment rate on the Turkish economy, where unemployment affected both labour productivity and real wages. While a bi-directional causality was found between labour productivity and unemployment, a unilateral causality was observed between unemployment and real wages. Unemployment causes real wages, but there is no evidence of reversal causation.

The paper examines sustainability of budget deficits and dynamic linkages between government revenues and expenditures in five major South Asian economies, namely India, Pakistan, Bangladesh, Srilanka and Nepal for period 1985-2014. The study contributes to the literature by combining individual-country analysis with recent panel data approaches for robustness of results. Our results support existence of long-run relationship between government revenues and expenditures for the countries in a specification allowing for unknown structural break. The size of slope parameter obtained from Dynamic Ordinary Least Squares is however significantly less than one except for Bangladesh indicating incoherence with ‘strong’ sustainability of deficits. The long run causality analysis lends support to ‘spend-tax hypothesis’ for India, Bangladesh, Pakistan and Srilanka and ‘tax- spend hypothesis’ in case of Nepal. From perspective of design of fiscal consolidation programmes, this implies that adjustment of revenues would be optimal solution to control spending in Nepal while control of expenditure would be effective in case of India, Bangladesh, Pakistan and Srilanka. The results from Pedroni (1999) and Westerlund (2007) panel cointegration tests and block exogeniety and DumitrescuHurlin (2012) panel causality tests are broadly in conformity with the time series results.

The paper examines sustainability of public finances for five major South Asian economies namely, India, Pakistan, Bangladesh, Sri Lanka and Nepal for period 1985-2014. The results of Gregory–Hansen (1996) and Carrion-i-Silvestre and Sanso (2006) tests confirm presence of long-run relationship between government revenue and expenditure for all the countries. The ARDL estimates of fiscal reaction function indicate positive long-run response of primary balance to rising public debt ratio in case of India, Bangladesh, Pakistan and Sri Lanka. The empirical results thus demonstrate coherence with intertemporal budget constraint for the countries. However, except for Bangladesh, sustainability exists only in weak form underscoring the need to reinforce commitments to long-term fiscal discipline.

This study explores the methods to de-trend the smooth structural break processes while conducting the unit root tests. The two most commonly applied approaches for modelling smooth structural breaks namely the smooth transition and the Fourier functions are considered. We perform a sequence of power comparisons among alternative unit root tests that accommodate smooth or sharp structural breaks. The power experiments demonstrate that the unit root tests utilizing the Fourier function lead to unexpected results. Furthermore, through simulation studies, we investigate the source of such unexpected outcomes. Moreover, we provide the asymptotic distribution of two recently proposed unit root tests, namely Fourier-Augmented Dickey–Fuller (FADF) and Fourier-Kapetanios, Shin and Shell (FKSS), which are not given in the original studies. Lastly, we find that the selection of de-trending function is pivotal for unit root testing with structural breaks.

Linear relations, containing measurement errors in input and output data, are considered. Parameters of these so-called errors-in-variables models can change at some unknown moment. The aim is to test whether such an unknown change has occurred or not. For instance, detecting a change in trend for a randomly spaced time series is a special case of the investigated framework. The designed changepoint tests are shown to be consistent and involve neither nuisance parameters nor tuning constants, which makes the testing procedures effortlessly applicable. A changepoint estimator is also introduced and its consistency is proved. A boundary issue is avoided, meaning that the changepoint can be detected when being close to the extremities of the observation regime. As a theoretical basis for the developed methods, a weak invariance principle for the smallest singular value of the data matrix is provided, assuming weakly dependent and non-stationary errors. The results are presented in a simulation study, which demonstrates computational efficiency of the techniques. The completely data-driven tests are illustrated through problems coming from calibration and insurance; however, the methodology can be applied to other areas such as clinical measurements, dietary assessment, computational psychometrics, or environmental toxicology as manifested in the paper.

Through its latest economic model, Malaysia has outlined ‘sustainability’ as the key element to achieve the Vision 2020 – to become a high-income nation by year 2020. This study analyzed the possible factors affecting sustainable development path in Malaysia using the Adjusted Net Savings (ANS) indicator; as projected by World Bank from 1990s. We firstly conducted the ‘Structural break-unit root tests’ to assume stationarity of series with the possible presence of economic shocks during the period of 1972 to 2011. For model estimation, we applied the ARDL technique to find the cointegration between money supply (LFIN), nonrenewable natural resource (fuels, ores and metals) exports (LNR), trade openness (LTRD) and urban population (LURB) with ANS values (LANS). In the short-run, LFIN and LTRD have significant negative impact on LANS while in long run, LNR and LURB tend to have significant negative impact on economic sustainability in Malaysia.

There are a number of studies focusing on the relationship between the tobacco consumption and unemployment rate in Turkey. Therefore, this study contributes to the literature because the relationship between tobacco tax and unemployment rate has not been studied before. The objective of this study is to determine the relationship between the tobacco tax and unemployment rate in Turkey over the period 2006:1-2015:7. In this context, Unit root tests have been exploited to check the integration order of the variables, and the Autoregressive Distributed Lag Model including structural breaks is employed to explain the long-run relationship between the tobacco tax and unemployment rate. The findings of this study show that while an increase in unemployment rate is to raise tobacco tax in the long-run, an increase in unemployment rate is to decrease tobacco tax in the short-run.

Sample size of data, presence of structural break, location and magnitude of potential break, and having with near integrated process might affect the performance of cointegration tests. Engle-Granger (EG) and Johansen Cointegration tests may have erroneous results since they do not take into account possible structural break unlike Gregory - Hansen (GH) cointegration test. In this study, it is argued that the suitable choice of cointegration tests is quite complex, since outcomes of these tests are very sensitive to specifying these properties. The performance of cointegration tests is compared to each other underlying properties. This study presents how standard residual based tests- Engle-Granger and Gregory-Hansen- for cointegration can be implemented if series is near integrated, that is close to a unit root process. For assessing the finite sample performance of these tests, a Monte-Carlo experiment showed that both cointegration tests have relatively better size and power properties depend on break point, break magnitude, sample size of time series and the hypothesized value of AR(1) parameter. To illustrate the findings of the paper, a financial data is analyzed. The practitioners should be careful about the hypothesized value of AR(1) parameter which represents dependency degree of the data. If the autoregressive parameters is very close to one and the break magnitude is high, any test is acceptable for moderate to large sample size. However, one might need very large sample size to have a good power and actual size of the test. Additionally, GH test becomes liberal test unlike EG test as the magnitude of structural break increases.

In this paper, we examine how the unit root for stock market series should be modeled. We employ the Narayan and Liu (2015) trend GARCH-based unit root and its variants in order to more carefully capture the inherent statistical behavior of the series. We utilize daily, weekly and monthly data covering nineteen countries across the regions of America, Asia and Europe. We find that the nature of data frequency matters for unit root testing when dealing with stock market data. Our evidence also suggests that stock market data is better modeled in the presence of structural breaks, conditional heteroscedasticity and time trend.

The paper employs asymmetric causality test based on Toda-Yamamoto (1995) causality approach to further investigate the causal relationship between exchange rate and inflation differentials in Brunei, Malaysia and Singapore. We simulate critical values based on leverage bootstrapping and asymmetric causality test from the underlying empirical data. The results are compared among the Granger asymptotic chi-square, the MWALD leverage bootstrapped distributions and asymmetric causality test. The reported conflicting findings proved the existence of size distortion and nuisance parameter estimates when the traditional Granger approach is applied. The results from Toda-Yamamoto with asymmetric causality test establish the existence of Granger causality running from positive cumulative exchange rate shocks to positive cumulative shocks in inflation differentials for Brunei and Malaysia. However, the asymmetric causality for Singapore runs from both positive and negative cumulative domestic inflation shocks to positive and negative exchange rate shocks respectively. The policy implication of the findings is that a strong price stabilization policy during both good and bad times can stabilize exchange rate fluctuations in Singapore whereas; formulation of effective exchange rate policy can only achieve price stability in Brunei and Malaysia during good period.

The 2007–2008 financial crisis had severe consequences on the global economy and an intriguing question related to the crisis is whether structural breaks in the credit market can be detected. To address this issue, we chose firms’ credit rating transition dynamics as a proxy of the credit market and discuss how statistical process control tools can be used to surveil structural breaks in firms’ rating transition dynamics. After reviewing some commonly used Markovian models for firms’ rating transition dynamics, we present several surveillance rules for detecting changes in generators of firms’ rating migration matrices, including the likelihood ratio rule, the generalized likelihood ratio rule, the extended Shiryaev’s detection rule, and a Bayesian detection rule for piecewise homogeneous Markovian models. The effectiveness of these rules was analyzed on the basis of Monte Carlo simulations. We also provide a real example that used the surveillance rules to analyze and detect structural breaks in the monthly credit rating migration of U.S. firms from January 1986 to February 2017.

This paper develops the generalized causality algorithm and applies it to a multitude of data from the fields of economics and finance. Specifically, our parameter-free algorithm efficiently determines the optimal non-linear mapping and identifies varying lead–lag effects between two given time series. This procedure allows an elastic adjustment of the time axis to find similar but phase-shifted sequences—structural breaks in their relationship are also captured. A large-scale simulation study validates the outperformance in the vast majority of parameter constellations in terms of efficiency, robustness, and feasibility. Finally, the presented methodology is applied to real data from the areas of macroeconomics, finance, and metal. Highest similarity show the pairs of gross domestic product and consumer price index (macroeconomics), S&P 500 index and Deutscher Aktienindex (finance), as well as gold and silver (metal). In addition, the algorithm takes full use of its flexibility and identifies both various structural breaks and regime patterns over time, which are (partly) well documented in the literature.

In the last two decades many countries have been starting to employ Inflation Targeting Framework (ITF) as their main monetary policy framework. This is done to achieve an objective of anchoring public expectation on inflation which in the end will steer the price level movement towards ITF’s ultimate target of relatively low and stable inflation rate. By conducting Difference-in-Difference method on panel data consisting of five countries implementing ITF since 2001 and twenty-one selected non-ITF countries for period 1990-2010, it is statistically proved that ITF adoption has a significant effect on inflation. In case of Indonesia, through Structural Break approach, the implementation of ITF since 2005 is also proved able to lower and stabilize inflation rate.

This paper analyzes the concept of structural break in the regional economic development. To meet the goal a literature review was done in seeking to explain how regional economic development happens and how economies transform their sectorialstructures. The processes of structural break leads into a cumulative movement in strengthening the economy forward or rewindthe regions. The progress can both be stimulated by the growth of the economics activities basis for actions linked directly to the local community.

 Government subsidies are one of the most important challenges in Iranâs economy, especially concerning the field of energy. The main objective of this paper is to examine the impact of natural gas price shocks on consumption of Semnan household Gas subscribers. Thus , the function o f household consumption of natural gas customers in Semnan city was estimated by Generalized Moments Method (GMM), during April 1385 and March 1391. Variables consisted are natural gas prices, lag of per capita consumption, temperature, lag of per capita income, the price of electricity. According to the estimated price and income elasticity, consumers have significant sensitivity to changes in natural Gas prices however structural break has not been observed in the pattern of natural Gas consumption.

Günümüzde, enerji sosyal ve ekonomik gelişmenin en temel girdilerinden birisi haline gelmiştir. Kömür, doğalgaz petrol vb. enerji kaynaklarının sınırlı olduğu gerçeği göz önünde bulundurulursa, enerji kaynaklarının verimli kullanılması gerekliliği yadsınamaz. Ülkelerin enerji kullanımı ile alakalı geleceği göz ardı etmeyen, sağlıklı ve kararlı politikalar üretmesi gerekmektedir. Büyük ölçekli sanayi tesislerinin üretim yapabilmesi için enerji vazgeçilmez bir üretim faktörü durumundadır. Büyümeye sağladığı katkı, enerjinin bir gelişmişlik ölçütü olarak kullanılmasına olanak sağlamıştır. Bu yüzden gelişmiş ülkeler enerji üretim ve tüketimine büyük önem vermektedir. Artan bu öneminden dolayı enerji tüketimi ve ekonomik büyüme arasındaki ilişki birçok çalışmaya konu olmuştur. Türkiye gibi enerji üretimi, enerji tüketimini karşılayamayan ülkeler için ise durum çok daha stratejik politikaların gerekli olduğunu göstermektedir. Dünya’nın en pahalı petrolünün satıldığı ülkemizde, petrol, doğalgaz ve elektrik gibi büyük öneme sahip girdiler üzerine getirilen vergilerin, üretici maliyetleri üzerine etkilerinin detaylı bir biçimde ele alınması gerekmektedir. Enerji maliyetlerinin çok arttığı bir ortamda, küresel rekabette dezavantajlı duruma düşen üreticiler, sadece yerel Pazar için ürün üretebilir, dolayısı ile üretim miktarında gözle görülür bir azalma meydana gelebilir.Bu çalışmanın amacı, Türkiye’de 1970-2009 dönemleri arasında yıllık verilerle, enerji tüketimi ile ekonomik büyüme arasındaki ilişkiyi yapısal kırılmalı modeller aracılığı ile incelemektir. Çalışmada kullanılan verilerden Reel Gayrı Safi Yurt İçi Hasıla, Gayrı Safi Sermaye oluşumu ve İhracat verileri Dünya Bankası’nın web sitesinden, Toplam Enerji Tüketimi verileri ise Dünya Enerji Konseyi’nin web sitesinden alınmıştır. Bunun için öncelikli olarak Zivot-Andrews Z-A yapısal kırılmalı birim kök testi uygulanmış olup, serilerin birinci farkında I 1 durağan oldukları tespit edilmiştir. Z-A birim kök testinden sonra Gregory-Hansen eşbütünleşme analizi yapılmış, seriler arasında uzun dönemde eşbütünleşme bulunmuştur. Bulunan bu eşbütünleşme seriler arasında en az bir nedensellik ilişkisinin olabileceğini göstermiştir. Granger nedensellik analizi sonucunda, Reel Gayrı Safi Yurt İçi Hasıla’dan sermayeye, enerji tüketiminden sermayeye, ihracattan Reel Gayrı Safi yurt İçi Hasıla’ya, ihracattan enerji tüketimine ve yine ihracattan sermayeye doğru tek yönlü nedensellik ilişkisi bulunmuş olup, buna karşın enerji tüketimi ile ekonomik büyüme arasında herhangi bir nedensellik ilişkisine rastlanmamıştır.

ÖZ: Çalışma ARFIMA-FIGARCH modelleri yardımıyla Türkiye hisse senedi piyasası getirilerinde ikili uzun hafıza özelliğinin varlığını incelemekte dolayısıyla zayıf formda etkin piyasa hipotezini test etmektedir. Bu amaçla kullanılan veri 2010-2013 dönemi Borsa İstanbul (BIST) için günlük hisse senedi kapanış fiyatlarını içermektedir. Öncelikle ortalama ve oynaklıktaki uzun hafızanın varlığı ayrı olarak incelenmiştir. ARFIMA modeli sonuçları BIST getirileri için ortalamada uzun hafıza özelliği gösterirken, getiri oynaklıklarındaki uzun hafızanın varlığı için FIGARCH modeli de istatistiksel olarak anlamlı sonuçlar vermiştir. İkinci olarak, ortalama ve oynaklıktaki birlikte uzun hafıza özelliği ARFIMA-FIGARCH modeli ile değerlendirilmiştir. Sonuç olarak, ortalamada uzun hafızanın varlığına dair bir bulgu elde edilemezken, oynaklığın öngörülebilir bir yapı gösterdiği Türkiye borsası etkin bir piyasa değildir. Anahtar Kelimeler: ARFIMA-FIGARCH, İkili Uzun Hafıza, Oynaklık, Yapısal Kırılma, Etkin Piyasa Hipotezi. ABSTRACT: The study examines presence of dual long memory property in returns of Turkish Stock Market by using ARFIMA-FIGARCH model and, tests Weak Form Efficient Market Hypothesis. The data set consists of daily closing prices for the period 2010 to 2013 of Istanbul Stock Exchange. Firstly, long memory property in return and volatility has been investigated separately. FIGARCH model indicates statistically significant findings while the results of ARFIMA model display long memory dynamics in returns of BIST. Secondly, long memory in return and volatility has been evaluated simultaneously by using ARFIMA-FIGARCH model. Consequently, Turkish Stock Market is not Efficient Market because volatility shows forecastable structure while there have not been obtained any finding about presence of long memory in return. Keywords: ARFIMA-FIGARCH, Dual Long Memory, Volatility, Structural Break, Efficient Market Hypothesis.

The main purpose of this paper is to introduce a method for more accurately measurement of structural breaks’ impacts of money demand function using fuzzy set approach. Hence, we present a robust method in order to modeling endogenous structural breaks. To do this, first, we review the recent studies on modeling structural breaks in money demand using nonlinear transition functions and fuzzy set theory, then we examine theoretical basics of fuzzy sets, membership and transition functions. In this paper, we model the structural breaks in money demand function via fuzzy set theory by using transition function instead of membership functions. In this regard, after introducing a new transition function, we model the 1993 structural break of money demand in Iran using a binary dummy variable and various transition functions. The findings show that the AS transition function due to more flexibility provides more accurate results rather than binary dummy variable, exponential and logistic transition functions. In general, if the dependent variable of the model is stationary, use of the binary dummy variable for modeling structural breaks causes misspecification. Also, if the dependent variable is non-stationary, due to increasing shock effect, the use of binary dummy variable is wrong.

It is often reported in the forecast combination literature that a simple average of candidate forecasts is more robust than sophisticated combining methods. This phenomenon is usually referred to as the “forecast combination puzzle”. Motivated by this puzzle, we explore its possible explanations, including high variance in estimating the target optimal weights (estimation error), invalid weighting formulas, and model/candidate screening before combination. We show that the existing understanding of the puzzle should be complemented by the distinction of different forecast combination scenarios known as combining for adaptation and combining for improvement. Applying combining methods without considering the underlying scenario can itself cause the puzzle. Based on our new understandings, both simulations and real data evaluations are conducted to illustrate the causes of the puzzle. We further propose a multi-level AFTER strategy that can integrate the strengths of different combining methods and adapt intelligently to the underlying scenario. In particular, by treating the simple average as a candidate forecast, the proposed strategy is shown to reduce the heavy cost of estimation error and, to a large extent, mitigate the puzzle.

Hoy en día es una práctica estándar de trabajo empírico la aplicación de diferentes estadísticos de contraste de raíz unitaria. A pesar de ser un aspecto práctico, estos estadísticos poseen distribuciones complejas y no estándar que dependen de funcionales de ciertos procesos estocásticos y sus derivaciones representan una barrera incluso para varios econometristas teóricos. Estas derivaciones están basadas en herramientas estadísticas fundamentales y rigurosas que no son (muy) bien conocidas por econometristas estándar. El presente artículo completa esta brecha al explicar en una forma simple una de estas herramientas fundamentales la cual es el Teorema del Límite Central Funcional. Por lo tanto, este documento analiza los fundamentos y la aplicabilidad de dos versiones del Teorema del Límite Central Funcional dentro del marco de una raíz unitaria con un quiebre estructural. La atención inicial se centra en la estructura probabilística de las series de tiempo propuesta por Phillips (1987a), la cual es aplicada por Perron (1989) para estudiar los efectos de un quiebre estructural (asumido) exógeno sobre la potencia de las pruebas Dickey-Fuller aumentadas y por Zivot y Andrews (1992) para criticar el supuesto de exogeneidad y proponer un método para estimar un punto de quiebre endógeno. Un método sistemático para tratar con aspectos de eficiencia es introducido por Perron y Rodríguez (2003), el cual extiende el enfoque de Mínimos Cuadrados Generalizados para eliminar los componentes determinísticos de Elliot et al. (1996). Se presenta además una aplicación empírica.

This paper examines the existence of β-Convergence between per-capita incomes of selected Islamic countries. For this purpose, data over the period 1965-2006 and a time series approach proposed by Vogelsang (1998) are applied. Robustness of the estimated parameters to the presence of unit roots and/or serial correlations in the residuals is the main advantage of this method. The results show that per-capita income of most countries is converging to the average per-capita income of the selected Islamic countries, which provide evidence of β-Convergence. Cameroon, Indonesia, Malaysia, Niger, Chad, and Togo are the countries that have shown some forms of divergence either before the break date or after that. The estimated break dates are clustered and mostly related to the energy shocks in 1974, 1979, and 1986.

En este artículo se presenta evidencia empírica sobre la relación entreel consumo de energía y el PIB para Colombia, durante el periodo 1970-2009.Los resultados muestran que las series son no estacionarias; es decir, son I (1) de manera individual, adicionalmente, existe una relación de largo plazo entre dichas variables. A través de un VECM se estiman las elasticidades de corto y largo plazo para analizar la dinámica de ajuste. Los resultados muestran que en el corto plazo se mantiene la hipótesis de conservación pero que a largo plazo se evidencia una retroalimentación entre ambas variables. Se concluye que en Colombia no se evidencia una relación de consumo de energía y PIB en el corto plazo, por tanto, los hacedores de política pueden implementar estrategias encaminadas a la conservación de la energía.

Hyper inflation rates impose direct and indirect costs upon society. It has undesirable consequences that are caused by inflation uncertainty. In this regard, the following questions are raised: How do inflation rate and its uncertainty affect economic growth? Does the structural breakpoint affect relationship between inflation and growth rate? In this study the above questions are examined for the Iran's economy in period 1974-2007. For this purpose the regressive model is applied. In this model, growth rate of GDP depends on inflation rate, growth rate of the money supply, growth rate of the real gross fixed capital formation and inflation uncertainty. For the measuring inflation uncertainty Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used. Based on data analysis, structural break point occurs at inflation rate equal to 20 percent. Results show that the impact of inflation rate on economic growth is significantly negative but it minimizes at the rate of less than 20 percent and increases at the rate of more than 20 percent. Moreover, inflation uncertainty has significant and negative effect on growth.