scholarly journals The Identification of Precursor Regulation Impact on the Methamphetamine Market and Public Health Indicators in the Czech Republic: Time Series Structural Break Analysis

2020 ◽  
Vol 17 (21) ◽  
pp. 7840
Author(s):  
Benjamin Petruželka ◽  
Miroslav Barták
Keyword(s):  
Public Health ◽  
Time Series ◽  
Czech Republic ◽  
Structural Breaks ◽  
Structural Changes ◽  
Structural Break ◽  
Health Indicators ◽  
Drug Market ◽  
Test Framework ◽  
The Impact

Background: This study provides insight into the impact of methamphetamine precursor regulation, which is considered to be one of the most important tools of supply reduction and a tool with potential public health impact. Methods: It is based on a longitudinal and quasi-experimental design and it investigates the changes of methamphetamine precursor regulation in Czech Republic, which is treated as a natural experiment. The statistical analysis uses features from the generalized fluctuation test framework as well as from the F test framework to estimate structural changes in the methamphetamine-related arrests and nonfatal intoxications time series. Results: The analysis identified structural breaks in the majority of the methamphetamine drug market-related time series in the period related to the tightening of regulation. The results of this study show that methamphetamine precursor regulation was associated with the proliferation of international and organized crime groups and with no change in the overall number of arrests and nonfatal intoxications. Conclusions: The precursor regulation ceteris paribus plausibly leads to the change in drug supply towards more organized groups and to an increasing involvement of foreign nationals at the drug market and is not effective in suppressing the methamphetamine market and in reducing the public health indicator of nonfatal methamphetamine intoxications.

Potential Indicators for the Analysis of the Association between Public Health and Drug Market Policing in the Czech Republic: Review of Public Health Indicators

2020 ◽  
Keyword(s):  
Public Health ◽  
Time Series ◽  
Czech Republic ◽  
Data Collection ◽  
Health Indicators ◽  
Drug Market ◽  
Grey Zone ◽  
The Czech Republic ◽  
Public Health Indicators ◽  
Basic Characteristics

BACKGROUND: A number of studies show that an intensification of the policing of illicit drug markets impacts on public health. The impacts are largely seen as negative. AIMS: The aim of this article is to describe the basic characteristics of available data and data collection of selected indicators and to review the aspects related to data collection and its context that might influence the selected public health time series in the Czech Republic. The secondary aim is to provide recommendations for future data collection in the Czech public health statistics. METHODS: This work is based on research of the specialised databases, reviewing reports published by relevant institutions and additional and selective literature and grey zone materials search. RESULTS: The article provides a review of the basic data collection characteristics and identifies different aspects of data collection and its context that have the potential to influence the time series of selected indicators in three different areas: a) treatment entrants, b) non-fatal and fatal intoxications, and c) infectious diseases. CONCLUSIONS: The review may assist and facilitate informed analysis and interpretation of drug-related law enforcement indicators individually or in combination with other indicators, using time series analysis as well as comparative approaches.

Does tourism affect house prices in Turkey? Evidence from smooth structural break tests

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mustafa Ozan Yıldırım ◽  
Cagin Karul
Keyword(s):  
Structural Breaks ◽  
Structural Changes ◽  
House Prices ◽  
Structural Break ◽  
Negative Influence ◽  
Mortgage Lending ◽  
Content Type ◽  
Substantial Role ◽  
Causality Tests ◽  
The Impact

Purpose The purpose of this study is to examine the impact of tourism activities on house prices in Turkey from January 2010 to March 2020. Design/methodology/approach It is used newly developed cointegration and causality tests based on Fourier approximation. These methods consider smooth structural breaks and do not need to recognize a priori date number and/or form of breaks. Findings Empirical findings show that international tourism activities have a substantial role in the escalation of house prices in Turkey. Findings also indicate a rise in industrial production enhances house prices while the mortgage lending rate exhibits a negative influence on house prices. Additionally, the evidence from Fourier causality tests reveals the unilateral causal linkage from tourism to house prices. This situation also shows that the tourism sector has a substantial role in stabilizing house prices’ rapid rise as a policy implication. Originality/value Although a large number of papers have been analyzing the link between house prices and macroeconomic variables, this study eliminates the lack of papers examining the link between tourism and house prices in Turkey by using the new cointegration and causality methods that consider smooth structural changes.

scholarly journals A macro assessment of China effects on Malaysian exports and trade balances

2014 ◽  
Vol 7 (1) ◽  
pp. 18-37 ◽  
Author(s):  
Tze-Haw Chan ◽  
Hooi Hooi Lean ◽  
Chee-Wooi Hooy
Keyword(s):  
Trade Balance ◽  
Structural Breaks ◽  
Structural Break ◽  
Analytical Framework ◽  
Trade Integration ◽  
Content Type ◽  
Regional Collaboration ◽  
Long Run ◽  
Cointegration Tests ◽  
The Impact

Purpose – This paper aims to focus on the impact of China's export expansion on Malaysian monthly trading with to her 12 major trading partners over the liberalization era. Design/methodology/approach – The analytical framework comprises of both the export and trade balance models. Unit root and cointegration tests with break and error correction modeling are employed in the analyses. Findings – Regime shifts are evident in the long run where structural break(s) found mostly coincides with the Asia crisis and China's accession into WTO. While the income effects are more apparent in most cases, the real exchanges are rather insignificant and incorrectly signed for Malaysian bilateral trading. Besides, the trade balance estimation is generally more consistent that the Chinese exports have exhibited complementary effects in the long-run, mainly for advanced export destination such as Australia, Germany, Japan, the UK and the USA. On the whole, there is insufficient evidence to support the “PRC competitive threat”. Practical implications – The empirical evidence disfavors currency devaluation for current account correction and reveals that the fear for China effect might be over-projected. Closer regional collaboration and trade integration between the two nations are well expected. Originality/value – The paper assesses the China's crowding out effect and magnitudes of Malaysian export and trade balance elasticities with model specifications that consider structural breaks. The paper also assesses the macro dimension of income and real exchanges effects.

scholarly journals Testing of breakdates in agricultural prices of selected representatives of animal production

2012 ◽  
Vol 60 (7) ◽  
pp. 45-54
Author(s):  
Petra Bubáková
Keyword(s):  
Time Series ◽  
Structural Breaks ◽  
Structural Break ◽  
Animal Production ◽  
Economic Environment ◽  
Ar Model ◽  
Model Parameters ◽  
Agricultural Prices ◽  
Complex Models ◽  
Food Market

This paper deals with an investigation of breakdates in agricultural prices. A structural break has occurred if at least one of the model parameters has changed at some date. This date is a breakdate. Ignoring structural breaks in time series can lead to serious problems with economic models of time series. The aim is to determine the number and date of the breakdates in individual time series and connect them with changes in the market and economic environment. The time series of agricultural price relating to animal production, namely the prices of pork, beef, chicken, milk and eggs, are analyzed for the period from January 1996 to December 2011. The autoregressive model (AR) model of Box-Jenkins methodology and stability testing according to Quandt or Wald statistics are used for the purposes of this paper. Multiple breakdates are found in the case of eggs (September 1998, May 2004), milk (October 1999, December 2007) and chicken (October 2002, February 2005) prices. One breakdate was detected in the prices of beef (April 2002) and none in the case of pork prices. The results show the importance of multiple breakdate testing. The Quandt statistic provides one possible way of applying a multiple approach. All breakdates which were confirmed using these statistics can be associated with changes in the agri-food market and economic environment. Information about the date of changes in the time series can be used for other unbiased modelling in more complex models.

scholarly journals SEBUAH ALTERNATIF: INDEKS STUNTING SEBAGAI EVALUASI KEBIJAKAN INTERVENSI BALITA STUNTING DI INDONESIA

2021 ◽  
Vol 44 (1) ◽  
pp. 21-30
Author(s):  
Zenderi Wardani ◽  
Dadang Sukandar ◽  
Yayuk Farida Baliwati ◽  
Hadi Riyadi
Keyword(s):  
Public Health ◽  
Time Series ◽  
Sustainable Development Goals ◽  
Economic Productivity ◽  
Index Model ◽  
Development Goals ◽  
Evaluation Measure ◽  
The Impact ◽  
Children Under 5 ◽  
Dimension Index

The proportion of stunting above 20 percent indicates that there are still public health problems in Indonesia. The impact of stunting not only affects the stature but also affects the economic productivity of a country. The purpose of this study was to develop index models that are responsive stunting in children under-5 years in Indonesia. Development of the index model used mathematical formulations using the SDGs indicator and other relevant indicators. Aggregate data from 16-time series were selected from 34 provinces in Indonesia in the span of 4 years (2015 - 2018). Furthermore, the method of developing a stunting index in this study was carried out through the stages of standardization, weighting, aggregation and validation. The results showed that the stunting index model is an evaluation measure that is responsive to stunting interventions in infants (0-56 months) in Indonesia. The national stunting index from 2015 to 2018 increased although it was still in the medium category with index values of 69.77, 70.29, 70.30 and 72.74, respectively. This study recommended an increase in efforts to achieve dimension index values in the development pillars of environmental and economical, especially in the eastern regions of Indonesia and the divided provinces.ABSTRAK Proporsi stunting lebih dari 20 persen menunjukkan bahwa masih terdapat masalah kesehatan masyarakat di Indonesia. Dampak stunting tidak hanya mempengaruhi perawakan tetapi juga mempengaruhi produktifitas ekonomi suatu negara. Sebuah model sederhana dan responsif dalam bentuk indeks stunting dapat menjadi bagian dari pilar rencana aksi intervensi stunting tersebut di atas. Model indeks stunting pun diharapkan dapat membantu pengambil keputusan (decision maker) menyusun formulasi, implementasi dan evaluasi kebijakan dalam penanggulangan stunting untuk masa yang akan datang. Tujuan penelitian ini adalah untuk mengembangkan model indeks stunting responsif pada anak balita di Indonesia. Pengembangan model indeks menggunakan formulasi matematis dengan menggunakan indikator Sustainable Development Goals (SDGs) dan indikator terkait lainnya. Data agregat dari 16 time series dipilih dari 34 provinsi di Indonesia dalam kurun waktu 4 tahun (2015 - 2018). Selanjutnya metode pengembangan indeks stunting pada penelitian ini dilakukan melalui tahapan standardisasi, pembobotan, agregasi dan validasi. Hasil penelitian menunjukkan bahwa model indeks stunting pada penilitian ini merupakan ukuran evaluasi yang tanggap terhadap intervensi stunting pada bayi (0-56 bulan) di Indonesia. Indeks stunting nasional dari tahun 2015 sampai 2018 mengalami peningkatan meskipun masih dalam kategori sedang dengan nilai indeks masing-masing 69,77, 70,29, 70,30 dan 72,74. Studi ini merekomendasikan peningkatan upaya pencapaian nilai indeks dimensi pada pilar pembangunan lingkungan dan ekonomi khususnya di wilayah timur Indonesia dan daerah provinsi pemekaran.Kata kunci: Indeks stunting, evaluasi kebijakan, anak balita

scholarly journals COVID-19: A Comparison of Time Series Methods to Forecast Percentage of Active Cases per Population

2020 ◽  
Vol 10 (11) ◽  
pp. 3880 ◽  
Author(s):  
Vasilis Papastefanopoulos ◽  
Pantelis Linardatos ◽  
Sotiris Kotsiantis
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Time Series ◽  
Health System ◽  
Total Population ◽  
Outbreak Detection ◽  
Time Series Modeling ◽  
Learning Time ◽  
Raising Awareness ◽  
The Impact

The ongoing COVID-19 pandemic has caused worldwide socioeconomic unrest, forcing governments to introduce extreme measures to reduce its spread. Being able to accurately forecast when the outbreak will hit its peak would significantly diminish the impact of the disease, as it would allow governments to alter their policy accordingly and plan ahead for the preventive steps needed such as public health messaging, raising awareness of citizens and increasing the capacity of the health system. This study investigated the accuracy of a variety of time series modeling approaches for coronavirus outbreak detection in ten different countries with the highest number of confirmed cases as of 4 May 2020. For each of these countries, six different time series approaches were developed and compared using two publicly available datasets regarding the progression of the virus in each country and the population of each country, respectively. The results demonstrate that, given data produced using actual testing for a small portion of the population, machine learning time series methods can learn and scale to accurately estimate the percentage of the total population that will become affected in the future.

On a Simple Graphical Approach to Modelling Economic Fluctuations with an Application to United Kingdom Price Inflation, 1265 to 2005

2006 ◽  
Vol 1 (1) ◽  
pp. 103-128
Author(s):  
W. S. Chan ◽  
M. W. Ng ◽  
H. Tong
Keyword(s):  
Time Series ◽  
United Kingdom ◽  
Structural Changes ◽  
Linear Models ◽  
Stochastic Modelling ◽  
Economic Time Series ◽  
Price Inflation ◽  
Non Linear ◽  
Economic Time ◽  
The Impact

ABSTRACTStructural instability in economic time series is widely reported in the literature. It is most prevalent in such series as price indices and inflation related data. Many methods have been developed for analysing and modelling structural changes in a univariate time series model. However, most of them assume that the data are generated by one fixed type (linear or non-linear) of the time series processes. This paper proposes a strategy for modelling different segments of an economic time series by different linear or non-linear models. A graphical procedure is suggested for detecting the model change points. The proposed procedure is illustrated by modelling annual United Kingdom price inflation series over the period 1265 to 2005. Stochastic modelling of inflation rates is an important topic to actuaries for dealing with long-term index linked insurance business. The proposed method suggests dividing the U.K. inflation series into four segments for modelling. Inflation projections based on the latest segment of the data are obtained through simulations. To get a better understanding of the impact of structural changes on inflation projections we also perform a forecasting study.

scholarly journals Speed of Reversion to PPP with Structural Breaks for Brazilian Cities

2018 ◽  
Vol 10 (4) ◽  
pp. 15
Author(s):  
Felipe S. Bastos ◽  
Elano F. Arruda ◽  
Rafael B. Barbosa ◽  
Roberto T. Ferreira
Keyword(s):  
Purchasing Power Parity ◽  
Half Life ◽  
Structural Breaks ◽  
Structural Changes ◽  
Structural Break ◽  
Convergence Speed ◽  
Purchasing Power ◽  
Power Parity ◽  
Relative Prices

This article analyzes the effect of introducing structural breaks in calculating the convergence speed of relative prices for Brazilian cities in the period from 1991.01 to 2016.11. Three structural break dates were endogenously chosen (1996.02, 2001.12 and 2010.10) and they represent different situations of the Brazilian economy, with impacts on intra-national relative prices. The convergence speed, measured by the half-life, declined by approximately 77% after controlling for these structural changes. The result was robust to changes in numeraire both for calculation of the half-life and estimation of the structural break dates, and indicates the importance of considering structural breaks in calculating intra-national purchasing power parity, as found in other studies.

Random order autoregressive time series model with structural break

2020 ◽  
Vol 15 (3) ◽  
pp. 225-237
Author(s):  
Saurabh Kumar ◽  
Jitendra Kumar ◽  
Vikas Kumar Sharma ◽  
Varun Agiwal
Keyword(s):  
Time Series ◽  
Structural Breaks ◽  
Time Series Data ◽  
Structural Break ◽  
Random Order ◽  
Real Data ◽  
Series Data ◽  
Model Parameters ◽  
Multiple Time ◽  
Multiple Time Points

This paper deals with the problem of modelling time series data with structural breaks occur at multiple time points that may result in varying order of the model at every structural break. A flexible and generalized class of Autoregressive (AR) models with multiple structural breaks is proposed for modelling in such situations. Estimation of model parameters are discussed in both classical and Bayesian frameworks. Since the joint posterior of the parameters is not analytically tractable, we employ a Markov Chain Monte Carlo method, Gibbs sampling to simulate posterior sample. To verify the order change, a hypotheses test is constructed using posterior probability and compared with that of without breaks. The methodologies proposed here are illustrated by means of simulation study and a real data analysis.

scholarly journals The Impact of Public Investment on Private Investment: Evidence from India

2016 ◽  
Vol 41 (4) ◽  
pp. 288-307 ◽  
Author(s):  
Pradyumna Dash
Keyword(s):  
Structural Breaks ◽  
Public Investment ◽  
Structural Break ◽  
Private Investment ◽  
Crowding Out ◽  
Base Line ◽  
Public Infrastructure ◽  
Executive Summary ◽  
Short Run ◽  
The Impact

Executive Summary This paper estimates the impact of public investment on private investment in India during 1970-2013 using ARDL procedure developed by Pesaran and Shin (1999) and Pesaran, Shin, and Smith (2001) by incorporating endogenously determined structural break in the model. The base line result implies that a 1 per cent increase in public investment as a ratio to GDP leads to 0.81 per cent and 0.53 per cent decrease in private investment as a ratio to GDP in the long run (about 4 to 5 years) and short run (about 2 to 3 years), respectively, after controlling for economic conditions. To address the concern that the results may be driven by government consumption expenditure, fiscal deficit, or inadequate infrastructure, the analysis was repeated by estimating the investment function after including these variables and similar results were obtained. The investment regression was also estimated for a shorter sample period (1978–2013) to get the same result. It is observed that the crowding out effect of public investment on private investment has dampened during the post-liberalization period. The results also reveal that a “market friendly” incumbent and an increase in foreign direct investment dampen the magnitude of the crowding out effect of public investment. Formal tests were conducted to examine whether the crowding out effect was driven by political uncertainty and political business cycle channels but no evidence for the same is found. The results also reveal that public infrastructure (represented by kms of roads per capita) has a positive effect on private investment in the short run. This is similar to the findings by Blejer and Khan (1984) that while public infrastructure investment is complementary to private investment, other kinds of public investment lead to crowding out of private investment. This suggests that public investment should be more focused on goods and services which are enjoyed or consumed by many consumers simultaneously and non-excludable in nature with significant positive externalities. In this model, a single endogenously determined structural break was included and the possibility of multiple breaks was excluded. There is a scope to increase multiple structural breaks and re-investigate the impact of public investment on private investment in India in future studies.

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