The Effect of Rainfall on Economic Growth in Thailand: A Blessing for Poor Provinces

Sangkhaphan, Siriklao; Yang, Shu

doi:10.3390/economies8010001

Cited by 21 publications

(12 citation statements)

References 40 publications

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“…According to World Bank [83], the contribution of agriculture, forestry, and fishing to Saudi Arabia's GDP was 2.23% in 2019. The negative impact of rainfall on economic growth is also substantiated by Sangkhaphan and Shu [60] who found rainfall in the case of Thailand negatively impacted on agriculture and service sectors, subsequently reducing economic growth. Higher rainfall is presumably conducive for economic growth, specifically in drought-prone countries.…”

Section: Plos Onementioning

confidence: 87%

“…Some studies have assessed the effects of rainfall fluctuation on sectoral and economic growth by using different analytical models. For example, Sangkhaphan and Shu [ 60 ] recently stated that rainfall has reduced growth at the national level through its significant negative effect on agriculture and service sectors, but helped the economies of poor parts of the world, which contradicts the results of Solaun and Cerdá [ 61 ]. Ayinde et al [ 62 ] has revealed in their study that an increase in rainfall has a positive effect on economic growth, which has been supported by Miguel et al [ 63 ], Ali [ 53 ], Cabral [ 64 ], and Odusola and Abidoye [ 2 ].…”

Section: Literature Reviewmentioning

confidence: 99%

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The effects of carbon emissions, rainfall, temperature, inflation, population, and unemployment on economic growth in Saudi Arabia: An ARDL investigation

2021

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Objective While macroeconomic and environmental events affect the overall economic performance of nations, there has not been much research on the effects of important macroeconomic and environmental variables and how these can influence progress. Saudi Arabia’s economy relies heavily on its vast reserves of petroleum, natural gas, iron ore, gold, and copper, but its economic growth trajectory has been uneven since the 1990s. This study examines the effects of carbon emissions, rainfall, temperature, inflation, population, and unemployment on economic growth in Saudi Arabia. Methods Annual time series dataset covering the period 1990–2019 has been extracted from the World Bank and General Authority of Meteorology and Environmental Protection, Saudi Arabia. The Autoregressive Distributed Lag (ARDL) approach to cointegration has served to investigate the long-run relationships among the variables. Several time-series diagnostic tests have been conducted on the long-term ARDL model to check its robustness. Results Saudi Arabia can still achieve higher economic growth without effectively addressing its unemployment problem as both the variables are found to be highly significantly but positively cointegrated in the long-run ARDL model. While the variable of carbon emissions demonstrated a negative effect on the nation’s economic growth, the variables of rainfall and temperate were to some extent cointegrated into the nation’s economic growth in negative and positive ways, respectively. Like most other nations the short-run effects of inflation and population on economic growth do vary, but their long-term effects on the same are found to be positive. Conclusions Saudi Arabia can achieve both higher economic growth and lower carbon emissions simultaneously even without effectively addressing the unemployment problem. The nation should utilize modern scientific technologies to annual rainfall losses and to reduce annual temperature in some parts of the country in order to achieve higher economic growth.

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Section: Plos Onementioning

confidence: 87%

Section: Literature Reviewmentioning

confidence: 99%

The effects of carbon emissions, rainfall, temperature, inflation, population, and unemployment on economic growth in Saudi Arabia: An ARDL investigation

2021

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“…However, there is little literature and empirical evidence for the short term, associated with Pandemic-type catastrophes such as COVID-19 with its daily dynamics. However, there are studies where epidemiological [26], climatic factors: rainfall [27,28], temperature [29][30][31] and environmental [32,33] are recognized, which emphasize the impact of economic activity. According to the SIR model, it has proven to be a good indicator of the evolution of COVID-19 [34].…”

Section: Literature Reviewmentioning

confidence: 99%

“…It is hypothetically assumed that there is an inverse causal relationship between temperature and economic activity [27][28][29][30][31]. Climate is considered a relevant variable that is correlated with COVID-19 [80,81], which increases the probability of risk of incidence and contagion [82] and indirectly affects economic activity.…”

Section: Plos Onementioning

confidence: 99%

Dynamics of the impact of COVID-19 on the economic activity of Peru

Varona

Gonzales

2021

PLoS ONE

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Background The COVID-19 virus impacts human health and the world economy, causing in Peru, more than 800 thousand infected and a strong recession expressed in a drop of -12% in its economic growth rate for 2020. In this context, the objective of the study is to analyze the dynamics of the short-term behavior of economic activity, as well as to explain the causal relationships in a Pandemic context based on the basic number of spread (Re) of COVID-19 per day. Methods An Autoregressive Distributed Lags (ARDL) model was used. Results A negative and statistically significant impact of the COVID-19 shock was found on the level of economic activity and a long-term Cointegration relationship with an error correction model (CEM), with the expected sign and statistically significant at 1%. Conclusion The Pandemic has behaved as a systemic shock of supply and aggregate demand at the macroeconomic level, which together have an impact on the recession or level of economic activity. The authors propose changing public health policy from an indiscriminate suppression strategy to a targeted, effective and intelligent mitigation strategy that minimizes the risk of human life costs and socioeconomic costs, in a context of uncertainty about the end of the Pandemic and complemented by economic, fiscal and monetary policies that mitigate the economic recession, considering the underlying structural characteristics of the Peruvian economy.

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“…The agriculture productivity primarily depends on climatic factors, namely, precipitation, temperature and evapotranspiration [3,4] . The precipitation (P), i.e., the quantity of rainfall, its intensity, and its distribution over an area during each cropping season can define the economy of any agriculture dependent country like India [5] . The precipitation and its pattern are also important for gaining an understanding of the micro-level availability of water, which in turn is useful for planning agricultural activities, and land and water development activities for future use [6] .…”

Section: Introductionmentioning

confidence: 99%

Long Term Spatio-temporal Variations of Seasonal and Decadal Aridity in India

Pinjarla

Joshi

et al. 2021

j. of atmos. sci. res.

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A comprehensive analysis of climate data (1958-2018) is carried out at the national scale in India to assess spatiotemporal variation in aridity. The aridity is analyzed using UNEP (United Nations Environment Programme) Aridity Index (AI), which is the ratio between Precipitation (P) and Potential Evapotranspiration (PET). Freely available Terra-Climate database, P and PET variables, offered an unprecedented opportunity for monitoring variations in AI and aridity index anomalies (AIA) at interseasonal and inter-decadal basis. The study also assesses longer term patterns of P and AI anomalies with vegetation anomalies. The results indicate that significant clustered areas with maximum dryness are located at west-central part of India, the state of Maharashtra. Overall, there is a gradual increase in the extent of arid zone during 60-year period and spatially maximum extent of percentage change in aridity area is observed. The change patterns of AI in India are largely driven by the changing patterns of precipitation. The maximum impact of decline in precipitation on AIA was observed during Kharif season frequently, for every 4-5 years during 1972-1992. The pattern repeated in the last few recent years (2013- 2018), the decline in precipitation resulted increased aridity. The study also reveals that the availability and usage of irrigation sources have increased from 2014 to 2018. Thus, despite of less precipitation positive vegetation has been resulted in this period. The findings are important to understand the impacts of climate change on land use pattern, and land and water resource management.

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The Effect of Rainfall on Economic Growth in Thailand: A Blessing for Poor Provinces

Cited by 21 publications

References 40 publications

The effects of carbon emissions, rainfall, temperature, inflation, population, and unemployment on economic growth in Saudi Arabia: An ARDL investigation

The effects of carbon emissions, rainfall, temperature, inflation, population, and unemployment on economic growth in Saudi Arabia: An ARDL investigation

Dynamics of the impact of COVID-19 on the economic activity of Peru

Long Term Spatio-temporal Variations of Seasonal and Decadal Aridity in India

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