investing in research and development spending (r&d) affects total factor productivity (tfp).recently new theories of economic growth have emphasized the relationship between r&d and tfpand also identified a number of channels through which a country’s r&d affects tfp of its tradepartner. this study seeks to estimate the effect of agricultural r&d and education spending and some...

The main purpose of this paper is to estimate the volatility in global fertilizer prices. The endogenous structural breakpoint unit root test and alternative volatility models, including the generalized autoregressive conditional heteroskedasticity (GARCH) model, Exponential GARCH (EGARCH) model, and GJR model are estimated for six global fertilizer prices and the crude oil price. Weekly data f...

This study uses the Autoregressive Distributed Lag (ARDL) model to study the dynamic determinant factors that influence both long and short-term international tourism demand in Cambodia from 12 countries. The annual time series data (1994–2013) are used in this study. The study finds that only the international tourism demand model of Australia, Canada, Thailand, the United Kingdom, and USA are...

The general purpose of a dynamic factor model (DFM) is to summarize large number time series into few common factors. In this paper we explore several DFMs on 80 granular, non-overlapping commercial property price indexes in the US, quarterly from 2001Q1 2017Q2. We examine nature and structure factors index forecasts that can be produced DFMs. consider specifications one four As major motivatio...

Absfrucf -A universal nearly efficient estimator is proposed for the first order autoregressive (AR) model where the probability distribution of the driving noise is unknown. The proposed estimator has an intuitively appealing relation to universal data compression and to universal tests for randomness. Index Terms -asymptotically efficient estimation, universal estimation, Cramer-Rao bound, Fi...

In nonlinear time series analysis, the mixture autoregressive model (MAR) is an effective statistical tool to capture multimodality of data. However, traditional methods usually need assume that error follows a specific distribution not adaptive dataset. This paper proposes via asymmetric exponential power distribution, which includes normal skew-normal generalized Laplace and uniform as specia...

Abstract This study re-investigates the money supply determination process for Japan. The methodology of this study, which differs from previous studies, is constructed on assumption potential nonlinear (asymmetric) relations between and monetary base via multiplier. To aim, autoregressive distributed lag (ARDL) model by Shin, Yu Greenwood-Nimmo, (2014) applied. allows us to examine endogeneity...

Recent advances in data analysis and processing methods can improve the ability of computational applications to perform complex steps different tasks. With progress information communication technologies (ICT), Blockchain-based for transaction smart contract agreement has become a new research area fields mathematics computation. Stability financial sector based on ICT is core component growin...