The impact of stock market development and inflation on economic growth in India: evidence using the ARDL bounds testing and VECM approaches

Pradhan, Rudra P.; Filho, Flávio de São Pedro; Hall, John H.

doi:10.1504/ijebr.2014.064118

Cited by 3 publications

(1 citation statement)

References 63 publications

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“…The stock index is also influential on the inflation rate. Pradhan et al (2014) and Prieto and Lee (2019) found a long-term relationship between the stock index and inflation. Apparently, when the stock market index rises, economic activity increases productivity.…”

Section: Introductionmentioning

confidence: 99%

Inflation forecasting using autoregressive distributed lag (ARDL) models

Ponziani

2023

JESP

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This study attempts to evaluate and compare the inflation-predicting performance of several ARDL models. Since there was no cointegration, the ARDL model does not employ an error correction term. Subsequently, model development showed that ARDL(2,2) should be used. Besides the formally developed model, some other more arbitrarily chosen ARDL models were also included, i.e., ARDL(1,1), ARDL(2,0), ARDL(1,0), ARDL(0,1), and ARDL(0,2). This research measures forecasting performance with inflation as the forecasting object. The duration of the monthly inflation statistics ranged from January 2011 to July 2022. The data were separated into two categories. The training data ranged between January 2011 and December 2021. After getting the appropriate parameters from the training data, the models generated projections from January 2022 to July 2022. The research determined that ARDL (1,0) was the most accurate inflation forecasting model, followed by ARDL (0,2) and formally constructed ARDL(2,2) finished in fourth place. This study suggests that the formal development of ARDL for forecasting purposes is unnecessary. Formal ARDL development is more appropriate for root cause analysis. In addition, the single autoregressive component indicates that most of the inflation value's information originated from the prior period. This suggests that the previous period's value is Indonesia's most significant predictor of inflation. The impact of greater period lags on inflation forecasting diminishes immediately.

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Section: Introductionmentioning

confidence: 99%