scholarly journals ASYMPTOTICALLY UNBIASED ESTIMATION OF AUTOCOVARIANCES AND AUTOCORRELATIONS WITH LONG PANEL DATA

2010 ◽  
Vol 26 (5) ◽  
pp. 1263-1304 ◽  
Author(s):  
Ryo Okui
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Unobserved Heterogeneity ◽  
Small Samples ◽  
Unbiased Estimation ◽  
Series Length ◽  
Cross Sectional ◽  
Long Run ◽  
The Individual ◽  
Time Invariant

An important reason for analyzing panel data is to observe the dynamic nature of an economic variable separately from its time-invariant unobserved heterogeneity. This paper examines how to estimate the autocovariances of a variable separately from its time-invariant unobserved heterogeneity. When both cross-sectional and time series sample sizes tend to infinity, we show that the within-group autocovariances are consistent, although they are severely biased when the time series length is short. The biases have the leading term that converges to the long-run variance of the individual dynamics. This paper develops methods to estimate the long-run variance in panel data settings and to alleviate the biases of the within-group autocovariances based on the proposed long-run variance estimators. Monte Carlo simulations reveal that the procedures developed in this paper effectively reduce the biases of the estimators for small samples.

scholarly journals Spectral Pitch Similarity is a Predictor of Perceived Change in Sound- as Well as Note-Based Music

2019 ◽  
Vol 2 ◽  
pp. 205920431984735
Author(s):  
Roger T. Dean ◽  
Andrew J. Milne ◽  
Freya Bailes
Keyword(s):  
Time Series ◽  
Piano Music ◽  
Individual Response ◽  
Discrete Events ◽  
Acoustic Intensity ◽  
Spectral Parameters ◽  
Cross Sectional ◽  
Perceived Change ◽  
Predictive Role ◽  
The Individual

Spectral pitch similarity (SPS) is a measure of the similarity between spectra of any pair of sounds. It has proved powerful in predicting perceived stability and fit of notes and chords in various tonal and microtonal instrumental contexts, that is, with discrete tones whose spectra are harmonic or close to harmonic. Here we assess the possible contribution of SPS to listeners’ continuous perceptions of change in music with fewer discrete events and with noisy or profoundly inharmonic sounds, such as electroacoustic music. Previous studies have shown that time series of perception of change in a range of music can be reasonably represented by time series models, whose predictors comprise autoregression together with series representing acoustic intensity and, usually, the timbral parameter spectral flatness. Here, we study possible roles for SPS in such models of continuous perceptions of change in a range of both instrumental (note-based) and sound-based music (generally containing more noise and fewer discrete events). In the first analysis, perceived change in three pieces of electroacoustic and one of piano music is modeled, to assess the possible contribution of (de-noised) SPS in cooperation with acoustic intensity and spectral flatness series. In the second analysis, a broad range of nine pieces is studied in relation to the wider range of distinctive spectral predictors useful in previous perceptual work, together with intensity and SPS. The second analysis uses cross-sectional (mixed-effects) time series analysis to take advantage of all the individual response series in the dataset, and to assess the possible generality of a predictive role for SPS. SPS proves to be a useful feature, making a predictive contribution distinct from other spectral parameters. Because SPS is a psychoacoustic “bottom up” feature, it may have wide applicability across both the familiar and the unfamiliar in the music to which we are exposed.

scholarly journals The Effect of Foreign Portfolio Equity Purchases on Security Returns in Kenya: Evidence from NSE Listed Financial Institutions

2017 ◽  
Vol 9 (4) ◽  
pp. 202
Author(s):  
Loice Koskei
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Stock Returns ◽  
Financial Institutions ◽  
Sampling Technique ◽  
Ordinary Least Squares ◽  
Capital Requirements ◽  
Cross Sectional ◽  
International Portfolio ◽  
Security Returns

Foreign portfolio inflows increase the liquidity and the volume of finance available for financial institutions. At the same time, as foreign portfolio inflows finances in part the capital requirements of local companies, it can also increase the competitiveness of these companies. A huge surge of the inflows can be very inflationary because this forces the Central Bank of Kenya to expand the country’s monetary base by releasing counterpart domestic currency which eventually feeds into the inflationary process. The main aim of this study was to find out the effect of international portfolio equity purchases on security returns of listed financial institutions in Kenya. The study population was 21 financial institutions listed on the Nairobi Securities Exchange. Using purposive sampling technique the study concentrated on 14 financial institutions. The research design of the study was causal as it is concerned more with understanding the connection between cause and effect relationships. The study adopted panel data regression using the Ordinary Least Squares (OLS) method where the data included time series and cross-sectional. A unit root test was carried in this study to examine stationarity of variables because it used panel data which combined both cross-sectional and time series information. Panel estimation results indicated that international portfolio equity purchases have no effect on stock returns of listed financial institutions in Kenya. The study recommended implementation of regulations and policies that would attract foreign portfolio equity inflows in financial institutions.

Limitations of Fixed-Effects Models for Panel Data

2019 ◽  
Vol 63 (3) ◽  
pp. 357-369 ◽  
Author(s):  
Terrence D. Hill ◽  
Andrew P. Davis ◽  
J. Micah Roos ◽  
Michael T. French
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Statistical Power ◽  
Unobserved Heterogeneity ◽  
Critical Discussion ◽  
Causal Inferences ◽  
Cross Sectional ◽  
Fixed Effects Models ◽  
Time Invariance ◽  
Type Ii Errors

Although fixed-effects models for panel data are now widely recognized as powerful tools for longitudinal data analysis, the limitations of these models are not well known. We provide a critical discussion of 12 limitations, including a culture of omission, low statistical power, limited external validity, restricted time periods, measurement error, time invariance, undefined variables, unobserved heterogeneity, erroneous causal inferences, imprecise interpretations of coefficients, imprudent comparisons with cross-sectional models, and questionable contributions vis-à-vis previous work. Instead of discouraging the use of fixed-effects models, we encourage more critical applications of this rigorous and promising methodology. The most important deficiencies—Type II errors, biased coefficients and imprecise standard errors, misleading p values, misguided causal claims, and various theoretical concerns—should be weighed against the likely presence of unobserved heterogeneity in other regression models. Ultimately, we must do a better job of communicating the pitfalls of fixed-effects models to our colleagues and students.

scholarly journals The Effect of Foreign Portfolio Equity Sales on Stock Returns in Kenya: Evidence from NSE Listed Financial Institutions

2017 ◽  
Vol 9 (4) ◽  
pp. 185
Author(s):  
Loice Koskei
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Stock Returns ◽  
Financial Institutions ◽  
Unit Root Test ◽  
Sampling Technique ◽  
Ordinary Least Squares ◽  
Cross Sectional ◽  
High Volatility ◽  
Study Population

Fluctuations of foreign portfolio equity intensify risk and unpredictability in financial institutions leading to high volatility. The main aim of this study was to find out the effect of foreign portfolio equity outflows on stock returns of listed financial institutions in Kenya. The study population was 21 financial institutions listed on the Nairobi Securities Exchange. Using purposive sampling technique the study concentrated on 14 financial institutions. The research design of the study was causal as it is concerned more with understanding the connection between cause and effect relationships. The study adopted panel data regression using the Ordinary Least Squares (OLS) method where the data included time series and cross-sectional. A unit root test was carried in this study to examine stationarity of variables because it used panel data which combined both cross-sectional and time series information. Panel estimation results indicated that foreign portfolio equity outflows have no effect on stock returns of listed financial institutions in Kenya. The study recommended implementation of policies that would curb foreign portfolio outflows in financial institutions in order to minimize reversals of foreign portfolio investments. 

ASYMPTOTIC PROPERTIES OF THE CUSUM ESTIMATOR FOR THE TIME OF CHANGE IN LINEAR PANEL DATA MODELS

2016 ◽  
Vol 33 (2) ◽  
pp. 366-412 ◽  
Author(s):  
Lajos Horváth ◽  
Marie Hušková ◽  
Gregory Rice ◽  
Jia Wang
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Common Factor ◽  
Asymptotic Properties ◽  
Real Data ◽  
Stationary Time Series ◽  
Model Errors ◽  
Cross Sectional ◽  
Monte Carlo Simulation Study ◽  
The Common

We consider the problem of estimating the common time of a change in the mean parameters of panel data when dependence is allowed between the cross-sectional units in the form of a common factor. A CUSUM type estimator is proposed, and we establish first and second order asymptotics that can be used to derive consistent confidence intervals for the time of change. Our results improve upon existing theory in two primary directions. Firstly, the conditions we impose on the model errors only pertain to the order of their long run moments, and hence our results hold for nearly all stationary time series models of interest, including nonlinear time series like the ARCH and GARCH processes. Secondly, we study how the asymptotic distribution and norming sequences of the estimator depend on the magnitude of the changes in each cross-section and the common factor loadings. The performance of our results in finite samples is demonstrated with a Monte Carlo simulation study, and we consider applications to two real data sets: the exchange rates of 23 currencies with respect to the US dollar, and the GDP per capita in 113 countries.

scholarly journals COMPETITION AND LEADER-FOLLOWER INTERACTIONS: PANEL ESTIMATES ON INDONESIAN BANKING

2016 ◽  
Vol 19 (1) ◽  
pp. 21-38
Author(s):  
Peter Abdullah ◽  
Pakasa Bary ◽  
Rio Khasananda ◽  
Rahmat Eldhie Sya’banni
Keyword(s):  
Panel Data ◽  
Unobserved Heterogeneity ◽  
Credit Market ◽  
Dynamic Panel Data ◽  
Dynamic Panel ◽  
Banking Competition ◽  
Full Sample ◽  
Panel Estimates ◽  
Time Invariant ◽  
Klein Model

This paper discusses banking competition and leader-follower relationship. Banking competition is investigated using some specification from Monti-Klein model that allows leader-follower (i.e. Stackleberg) relationship, the possibility of Cournot competition and other form of competition. We use monthly observations across 119 banks listed in Indonesia using the standard panel fixed effect methodology to absorb time-invariant unobserved heterogeneity and dynamic panel data to minimize the risks of endogeneity. The estimation suggests the leader-follower relationship among banks exist both on loan and deposit markets. The results are mostly consistent across different groups and on full sample estimates, although are quite different in magnitudes. While leader-follower relationship is dominantly occur in credit market, there are some evidence of simultaneous appearance of both leader-follower and Cournot interactions on the deposit market

scholarly journals The trade-off between GDP and CO2 emissions in poor countries: A dynamic common correlated effects approach for unbalanced panel data

2021 ◽  
Author(s):  
Quoc Khanh Duong
Keyword(s):  
Climate Change ◽  
Panel Data ◽  
Co2 Emissions ◽  
Growth Models ◽  
Cross Sectional ◽  
Poor Countries ◽  
Trade Offs ◽  
Long Run ◽  
Common Correlated Effects ◽  
Unbalanced Panel Data

Abstract In recent years, the term "climate change" has been increasingly receiving a lot of attention from scholars and policy makers, adversely affecting the lives of people (mostly of the poor) around the world in the present, and threatening the environment quality in the future. With many concerns about environmental degradation, countries tend to transform economic growth models causing negative impacts on the environment, especially for those in the stage of industrialization and modernization. This study was aimed at investigating the trade-offs between economic development and climate change among poor nations – the most affected by and most likely causing to climate change. By using a dynamic common correlated effects approach for unbalanced panel data which deals with cross-sectional dependency and time-series persistence, the paper showed that GDP is strongly correlated to CO2 emissions both in the short and long run, and one of the reasons is the use of CO2-generating energy sources.JEL classification: C23, O44, Q54

scholarly journals Is Living in Mwanza Region More Economically Better and Happier than Living in Kagera Region? Finite Mixture (FIMIX) Approach

2021 ◽  
pp. 12-26
Author(s):  
Ntogwa N. Bundala ◽  
Deus Dominic P. Ngaruko ◽  
Timothy M. Lyanga
Keyword(s):  
Panel Data ◽  
Survey Research ◽  
Psychological Factors ◽  
Unobserved Heterogeneity ◽  
Finite Mixture ◽  
Economic Opportunity ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Per Capita ◽  
The Cross

The study aimed to uncover the unobserved heterogeneity of the population in Mwanza and Kagera regions. The study examined if living in Mwanza region is more economically better and happier than living in Kagera region. The cross-sectional survey research used with the cross-sectional data from 211 individuals sampled randomly from 4 districts, Nyamagana and Misungwi from Mwanza region, and Bukoba and Muleba from Kagera region. The FIMIX-PLS used to analyse the data. The study found that the population of Mwanza and Kagera regions can be grouped into two mains classes which are class one with a lower annualised income below 1.5 TZS millions per capita and a lower mean score of fundamental psychological factors for happiness (FPFH) in comparing to the class two. The class two is characterised with a higher annualised income about 2.45 TZS millions per capita and a higher mean score of FPFH in comparing to class one. The study evidenced that respondents of Mwanza region have a higher annualised income and FPFH scores than respondents of Kagera region in each class. Therefore, the study concluded that living in Mwanza region is more economically better and happier than living in Kagera region. The study recommended the immigration to seek the economic opportunity and happiness, for example immigration from Kagera region to Mwanza region or nation to nation is encouraged. Moreover, further study recommended by using a panel data to attest the posed facts because this study limited to the cross-sectional data.

The Effects of Government System Fractionalization on Satisfaction With Democracy

2017 ◽  
Vol 6 (3) ◽  
pp. 593-611 ◽  
Author(s):  
Pablo Christmann ◽  
Mariano Torcal
Keyword(s):  
Time Series ◽  
Comparative Study ◽  
Opposite Effect ◽  
Cross Sectional ◽  
Individual Level ◽  
Satisfaction With Democracy ◽  
Institutional Determinants ◽  
The World ◽  
The Individual ◽  
The Comparative Study

Consensual-pluralistic institutional features of representative democracies have traditionally been associated with satisfaction with democracy (SWD). However, more recent studies report contradictory results on the effects of some of these institutional determinants on SWD. This article confirms these puzzling findings by showing that electoral proportionality increases SWD while other pluralistic factors such as government fractionalization produce the opposite effect. We illustrate this duality of counteracting effects by expanding the number of cases under study to different regions of the world in a comprehensive time-series cross-sectional sample of 58 democracies between 1990 and 2012. In the second part of the paper, we are able to reconfirm these findings at the individual level by employing survey data from the Comparative Study of Electoral Systems.

scholarly journals Are resilient factors increasing the risk for childhood psychological victimization?

2018 ◽  
Vol 6 (6) ◽  
pp. 1168-1173
Author(s):  
Dimitrinka Jordanova-Peshevska ◽  
Fimka Tozija
Keyword(s):  
Psychological Abuse ◽  
Statistical Significance ◽  
Significant Negative Correlation ◽  
Cross Sectional Study ◽  
Common Interest ◽  
Cross Sectional ◽  
Childhood Experiences ◽  
Long Run ◽  
The Individual ◽  
Psychological Victimization

Background: Understanding the resilient factors and why some children do well despite early adverse experiences is crucial, because it can inform more effective policies and programs that help more children reach their full potential.Aim: The main objective of the study is to describe the associations between psychological abuse in childhood and resilient risk factors on individual, relational, contextual level among adolescents in the country and see the probability of resiliency to predict psychological victimization.  Material and method: Cross-sectional study on two stage quota sample of 622 university students was applied in the study, including adolescents at first-year at the main public University “St Cyril and Methodius, Skopje”, from the 12 faculties in the country. Adverse Childhood Experiences Study International Questionnaires was used for collecting information on psychological abuse, while the individual, relational and contextual resilient factors were measured using the Child аnd Youth Resilience Measure - Youth version. The study was conducted from March to September 2017. Statistical significance was set up at p<0.05.Results: The results from the study have shown statistically significant negative correlation between exposure to psychological abuse in childhood and individual (rpb =-.159), relational (rpb =-.263), contextual factors (rpb = -.147), and resilience in total (rpb =-.232). The regressive model presents that 5.2% of the variance of the variable experienced psychological abuse is explained with resilience (F(1, 527)=28.909; p<.001), showing that resilience is negatively significant predictor for being psychologically abused in childhood (β=-.228; t=-5.377; p<.001).Conclusion: Supporting children by prevention means foster competence and prevent problems. Preventive programms represent developing protective factors in childhood, increasing competence and skills for the growth of resilience and decreasing the likelihood for developing psychopathology in adolescence and adulthood. It is of common interest of society for implementation of evidence based interventions with nurturing environments and in the long run setting up positive childhood platform  for future generations.

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