Is tracking and modeling Covid-19 infection dynamics for Bangladesh using daily data feasible? (Preprint)

2020 ◽  
Author(s):  
Karar Zunaid Ahsan ◽  
Rashida Ijdi ◽  
Peter Kim Streatfield
Keyword(s):  
Test Results ◽  
Infection Rates ◽  
Causality Test ◽  
Vector Autoregressive Models ◽  
Vector Autoregressive ◽  
Daily Number ◽  
Infection Dynamics ◽  
Daily Data ◽  
Daily Change ◽  
Testing Coverage

UNSTRUCTURED Given the low Covid-19 testing coverage in the country, this study tested whether the daily change in the number of new Covid-19 cases is due to increase (or decrease) in the number of tests done daily. We performed Granger causality test based on vector autoregressive models on Bangladesh case and test numbers between 8 March and 5 June 2020, using publicly available data. The test results show that the daily number of tests Granger-cause the number of new cases (p <0.001), meaning the daily number of new cases is perhaps due to an increase in test capacity rather than a change in the infection rates. From the results of this test we can infer that if the number of daily tests does not increase substantially, data on new infections will not give much information for understanding covid-19 infection dynamics in Bangladesh.

scholarly journals Is tracking and modeling Covid-19 infection dynamics for Bangladesh using daily data feasible?

2020 ◽  
Author(s):  
Karar Zunaid Ahsan ◽  
Rashida E Ijdi ◽  
Peter Kim Streatfield
Keyword(s):  
Test Results ◽  
Infection Rates ◽  
Causality Test ◽  
Vector Autoregressive Models ◽  
Vector Autoregressive ◽  
Daily Number ◽  
Infection Dynamics ◽  
Daily Data ◽  
Daily Change ◽  
Testing Coverage

AbstractGiven the low Covid-19 testing coverage in the country, this study tested whether the daily change in the number of new Covid-19 cases is due to increase (or decrease) in the number of tests done daily. We performed Granger causality test based on vector autoregressive models on Bangladesh’s case and test numbers between 8 March and 5 June 2020, using publicly available data. The test results show that the daily number of tests Granger-cause the number of new cases (p <0.001), meaning the daily number of new cases is perhaps due to an increase in test capacity rather than a change in the infection rates. From the results of this test we can infer that if the number of daily tests does not increase substantially, data on new infections will not give much information for understanding covid-19 infection dynamics in Bangladesh.

scholarly journals Do Stock Markets Have Any Impact on Real Economic Activity?

2016 ◽  
Vol 64 (1) ◽  
pp. 283-290
Author(s):  
Kateřina Krchnivá
Keyword(s):  
Stock Markets ◽  
Economic Activity ◽  
Granger Causality Test ◽  
The Other ◽  
Causality Test ◽  
Vector Autoregressive Models ◽  
Vector Autoregressive ◽  
The Real ◽  
The Relationship ◽  
Constant Prices

There is no doubt about the existence of connection between the stock markets and the real economic activity. Many researchers indicated that the stock markets causally affect the economic activity with the lag of three months. Contrary, the other group of researchers suggested, that these relationships are reversal, moreover some of them concluded that these relationships are reciprocal. The paper analyses the relationship between the stock markets and the economic activity in seven countries with the research objective to identify these relationships in relation of cause and effect. As the proxy of the stock markets are stock indices considered, while the economic activity is expressed by the Gross Domestic Product at constant prices. The correlation analysis and the Granger causality test applied on suggested vector autoregressive models are employed for the research in the paper. The paper concludes that stock markets may be considered as the significant predictor of the real economic activity with the lag of one quarter, however, there is no reciprocal links between them.

scholarly journals The drivers of economic growth in China and India: globalization or financial development?

2017 ◽  
Vol 16 (1) ◽  
pp. 54-84 ◽  
Author(s):  
Magda Kandil ◽  
Muhammad Shahbaz ◽  
Mantu Kumar Mahalik ◽  
Duc Khuong Nguyen
Keyword(s):  
Economic Growth ◽  
Financial Development ◽  
Emerging Market ◽  
Annual Data ◽  
Test Results ◽  
Causality Test ◽  
Content Type ◽  
China And India ◽  
Integration Test ◽  
The Impact

Purpose Using annual data from 1970 to 2013 for China and India, this paper aims to examine the impact of globalization and financial development on economic growth by endogenizing capital and inflation and drawing comparisons between the two fastest growing emerging market economies. Design/methodology/approach In the long run, co-integration test results indicate that financial development increases economic growth in China and India. Findings The results also reveal that globalization accelerates economic growth in India but, surprisingly, impairs economic growth in China, as it increases competition for exports. The results furthermore disclose that acceleration in capitalization and inflation, as a proxy for aggregate demand, are positively linked to economic growth in China and India. Originality/value Causality test results indicate that both financial development and economic growth are interdependent. In contrast, causality runs from higher economic growth to increased globalization in India, while the results do not support long-term causality between globalization and economic growth in China.

A Spatial Prior for Bayesian Vector Autoregressive Models

1999 ◽  
Vol 39 (2) ◽  
pp. 297-317 ◽  
Author(s):  
James P. LeSage ◽  
Anna Krivelyova
Keyword(s):  
Autoregressive Models ◽  
Vector Autoregressive Models ◽  
Vector Autoregressive

Fitting Multilevel Vector Autoregressive Models in Stan, JAGS, and Mplus

2021 ◽  
pp. 1-24
Author(s):  
Yanling Li ◽  
Julie Wood ◽  
Linying Ji ◽  
Sy-Miin Chow ◽  
Zita Oravecz
Keyword(s):  
Autoregressive Models ◽  
Vector Autoregressive Models ◽  
Vector Autoregressive

scholarly journals INTER-RELATIONSHIP BETWEEN THE HOUSING MARKET AND HOUSING FINANCE SYSTEM: EVIDENCE FROM MALAYSIA

2014 ◽  
Vol 18 (2) ◽  
pp. 138-150 ◽  
Author(s):  
Rosli Said ◽  
Alaistair Adair ◽  
Stanley McGreal ◽  
Rohayu Majid
Keyword(s):  
Housing Market ◽  
Granger Causality ◽  
Granger Causality Test ◽  
Housing Finance ◽  
Causality Test ◽  
Vector Autoregressive ◽  
Finance System

The Malaysian housing market and associated housing finance system have expanded significantly as a result of rapid urbanisation since the late 1980s. The key aspect of this paper is to analyse the inter-relationship between the housing market and housing finance system in Malaysia. The paper employs Vector Autoregressive approach and Granger Causality test to empirically investigate this inter-relationship. In Malaysia, no housing studies has actually looked into or used this approach to identify the inter-relationship between these two elements. The key findings show that there is a strong inter-relationship between the housing market and housing finance system. The direction of causality shows that there is a bi-directional relationship between the housing market and housing finance system. These inter-relationships provide evidence that sound performance of the sub-markets within the housing finance system is a determinant prerequisite of the robustness of the housing finance system, if a healthy performance of the housing market is to be achieved.

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