On the Constancy of Hedonic Wine Price Coefficients over Time

2019 ◽  
Vol 14 (2) ◽  
pp. 182-207 ◽  
Author(s):  
Benoît Faye ◽  
Eric Le Fur
Keyword(s):  
Time Series ◽  
Literature Review ◽  
Time Series Data ◽  
Hedonic Model ◽  
Series Data ◽  
Extensive Literature ◽  
Long Run ◽  
The Stability ◽  
Over Time ◽  
Jel Classifications

AbstractThis article tests the stability of the main hedonic wine price coefficients over time. We draw on an extensive literature review to identify the most frequently used methodology and define a standard hedonic model. We estimate this model on monthly subsamples of a worldwide auction database of the most commonly exchanged fine wines. This provides, for each attribute, a monthly time series of hedonic coefficients time series data from 2003 to 2014. Using a multivariate autoregressive model, we then study the stability of these coefficients over time and test the existence of structural or cyclical changes related to fluctuations in general price levels. We find that most hedonic coefficients are variable and either exhibit structural or cyclical variations over time. These findings shed doubt on the relevance of both short- and long-run hedonic estimations. (JEL Classifications: C13, C22, D44, G11)

scholarly journals Jonckheere–Terpstra–Kendall-based non-parametric analysis of temporal differential gene expression

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Hitoshi Iuchi ◽  
Michiaki Hamada
Keyword(s):  
Gene Expression ◽  
Time Series ◽  
Time Course ◽  
Time Series Data ◽  
Expression Patterns ◽  
Detection Methods ◽  
Series Data ◽  
Expression Levels ◽  
Over Time ◽  
Non Parametric

Abstract Time-course experiments using parallel sequencers have the potential to uncover gradual changes in cells over time that cannot be observed in a two-point comparison. An essential step in time-series data analysis is the identification of temporal differentially expressed genes (TEGs) under two conditions (e.g. control versus case). Model-based approaches, which are typical TEG detection methods, often set one parameter (e.g. degree or degree of freedom) for one dataset. This approach risks modeling of linearly increasing genes with higher-order functions, or fitting of cyclic gene expression with linear functions, thereby leading to false positives/negatives. Here, we present a Jonckheere–Terpstra–Kendall (JTK)-based non-parametric algorithm for TEG detection. Benchmarks, using simulation data, show that the JTK-based approach outperforms existing methods, especially in long time-series experiments. Additionally, application of JTK in the analysis of time-series RNA-seq data from seven tissue types, across developmental stages in mouse and rat, suggested that the wave pattern contributes to the TEG identification of JTK, not the difference in expression levels. This result suggests that JTK is a suitable algorithm when focusing on expression patterns over time rather than expression levels, such as comparisons between different species. These results show that JTK is an excellent candidate for TEG detection.

scholarly journals Evidence Graphs: Supporting Transparent and FAIR Computation, with Defeasible Reasoning on Data, Methods and Results

2021 ◽  
Author(s):  
Sadnan Al Manir ◽  
Justin Niestroy ◽  
Maxwell Adam Levinson ◽  
Timothy Clark
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Time Series Data ◽  
Predictive Analytics ◽  
Defeasible Reasoning ◽  
Series Data ◽  
Inference Rules ◽  
Deep Networks ◽  
Evidence Graph ◽  
Over Time

Introduction: Transparency of computation is a requirement for assessing the validity of computed results and research claims based upon them; and it is essential for access to, assessment, and reuse of computational components. These components may be subject to methodological or other challenges over time. While reference to archived software and/or data is increasingly common in publications, a single machine-interpretable, integrative representation of how results were derived, that supports defeasible reasoning, has been absent. Methods: We developed the Evidence Graph Ontology, EVI, in OWL 2, with a set of inference rules, to provide deep representations of supporting and challenging evidence for computations, services, software, data, and results, across arbitrarily deep networks of computations, in connected or fully distinct processes. EVI integrates FAIR practices on data and software, with important concepts from provenance models, and argumentation theory. It extends PROV for additional expressiveness, with support for defeasible reasoning. EVI treats any com- putational result or component of evidence as a defeasible assertion, supported by a DAG of the computations, software, data, and agents that produced it. Results: We have successfully deployed EVI for very-large-scale predictive analytics on clinical time-series data. Every result may reference its own evidence graph as metadata, which can be extended when subsequent computations are executed. Discussion: Evidence graphs support transparency and defeasible reasoning on results. They are first-class computational objects, and reference the datasets and software from which they are derived. They support fully transparent computation, with challenge and support propagation. The EVI approach may be extended to include instruments, animal models, and critical experimental reagents.

scholarly journals Political Stability and its Impact on Economic Growth of Pakistan (1988-2018): A Time Series Analysis

2020 ◽  
Vol 6 (1) ◽  
pp. 273-282
Author(s):  
Majid Hussain Phul ◽  
Muhammad Saleem Rahpoto ◽  
Ghulam Muhammad Mangnejo
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Time Series Data ◽  
Political Stability ◽  
Series Data ◽  
Explanatory Variables ◽  
Long Run ◽  
Short Run ◽  
The Impact ◽  
Positive Effect

This research paper empirically investigates the outcome of Political stability on economic growth (EG) of Pakistan for the period of 1988 to 2018. Political stability (PS), gross fixed capital formation (GFCF), total labor force (TLF) and Inflation (INF) are important explanatory variables. Whereas for model selection GDPr is used as the dependent variable. To check the stationary of time series data Augmented Dickey Fuller (ADF) unit root (UR) test has been used,  and whereas to find out the long run relationship among variables, OLS method has been used. The analysis the impact of PS on EG (EG) in the short run, VAR model has been used. The outcomes show that all the variables (PS, GFCF, TLF and INF) have a significantly positive effect on the EG of Pakistan in the long run period. But the effect of PS on GDP is smaller. Further, in this research we are trying to see the short run relationship between GDP and other explanatory variables. The outcomes show that PS does not have such effect on GDP in the short run analysis. While GFCF, TLF and INF have significantly positive effect on GDP of Pakistan in the short run period.

scholarly journals How applicable is export-led growth and import-led growth hypotheses to South African economy?

2015 ◽  
Vol 4 (2) ◽  
pp. 15-24
Author(s):  
Ntebogang Dinah Moroke ◽  
Molebogeng Manoto
Keyword(s):  
Economic Growth ◽  
South Africa ◽  
Adverse Effect ◽  
Time Series ◽  
South African ◽  
Time Series Data ◽  
Series Data ◽  
Long Run ◽  
Reserve Bank ◽  
Equilibrium Relationship

This paper investigated exports, imports and the economic growth nexus in the context of South Africa. The paper sets out to examine if long-run and causal relationships exist between these variables. Quarterly time series data ranging between 1998 and 2013 obtained from the South African Reserve Bank and Quantec databases was employed. Initial data analysis proved that the variables are integrated at their levels. The results further indicated that exports, imports and economic growth are co-integrated, confirming an existence of a long-run equilibrium relationship. Granger causal results were shown running from exports and imports to GDP and from imports to exports, validating export-led and import-led growth hypotheses in South Africa. A significant causality running from imports to exports, suggests that South Africa imported finished goods in excess. If this is not avoided, lots of problems could be caused. A suggestion was made to avoid such problematic issues as they may lead to replaced domestic output and displacement of employees. Another dreadful ramification may be an adverse effect on the economy which may further be experienced in the long-run.

Examining the Long Run Effects of Export, Import and FDI Inflows on the FDI Outflows from India: A Causality Analysis

2009 ◽  
Vol 10 (1) ◽  
pp. 65-88
Author(s):  
Nandita Dasgupta
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Driving Force ◽  
Time Series Data ◽  
Series Data ◽  
Causality Analysis ◽  
Fdi Inflows ◽  
Long Run ◽  
Time Series Data Analysis ◽  
Trade And Investment

The objective of this paper is to examine the effects of international trade and investment related macro economic variables, namely, exports, imports and FDI inflows on the outflows of FDI from India over 1970 through 2005. Using time series data analysis, the empirical part of the paper finds unidirectional Granger Causality from export and import to FDI outflows but no such causality exists from FDI inflows to the corresponding outflows from India. Results confirm the assumption that lagged imports and exports are a driving force of ing front.

Asset Quality and Deposit Money Banks Performance in Nigeria

2019 ◽  
Vol 1 (1) ◽  
pp. 38-47
Author(s):  
Mbatabbey Joy Ogboru
Keyword(s):  
Time Series ◽  
Financial Stability ◽  
Deposit Insurance ◽  
Time Series Data ◽  
Annual Reports ◽  
Series Data ◽  
Bank Performance ◽  
Long Run ◽  
Short Run ◽  
Asset Quality

This study investigate the relationship between asset quality and deposit money banks performance in Nigeria over a period of 30 years ranging from 1986 to 2016, utilizing time series data collected from the Nigeria deposit insurance corporation annual reports and accounts, CBN financial stability report and CBN statistically bulletin for various years. The variables of study includes return on asset (ROA) proxy for Deposit Money Bank performance in Nigeria, ratio of non-performing loan to total loan (NPL), ratio of liquid assets to total assets (LAT) and ratio of liquid assets to short term liabilities (LAS) as measures of asset quality. The study utilizes both the descriptive and econometric techniques to analyze the time series data. The result shows that there is a short run relationship between asset quality and deposit money bank performance in Nigeria. Also, the co-integration result reveals the presence of a long run relationship between asset quality and deposit money bank performance in Nigeria while the granger causality result shows evidence of causality between asset quality and deposit money bank performance in Nigeria. Based on this we conclude by saying that maintaining sound assets quality position is critical to the long term performance, survival and sustainability of DMBs in Nigeria.

scholarly journals Splendide Mendax: False Label Claims About High and Rising Alcohol Content of Wine

2015 ◽  
Vol 10 (3) ◽  
pp. 275-313 ◽  
Author(s):  
Julian M. Alston ◽  
Kate B. Fuller ◽  
James T. Lapsley ◽  
George Soleas ◽  
Kabir P. Tumber
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Time Series Data ◽  
Consumer Preferences ◽  
Series Data ◽  
Alcohol Content ◽  
Demand Shifts ◽  
Expert Ratings ◽  
Jel Classifications

AbstractAre wine alcohol labels accurate? If not, why? We explore the high and rising alcohol content of wine and examine incentives for false labeling, including the roles of climate, evolving consumer preferences, and expert ratings. We draw on international time-series data from a large number of countries that experienced different patterns of climate change and influences of policy and demand shifts. We find systematic patterns that suggest that rising wine alcohol content may be a nuisance by-product of producer responses to perceived market preferences for wines having more-intense flavours, possibly in conjunction with evolving climate. (JEL Classifications: D22, L15, L66, Q18, Q54).

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