Estimation and decomposition of food price inflation risk

2021 ◽  
Author(s):  
Kris Boudt ◽  
Hong Anh Luu
Keyword(s):  
Food Price ◽  
Price Inflation ◽  
Inflation Risk

scholarly journals Is Food Price Inflation Transitory? Empirical Evidence from Sri Lanka

2015 ◽  
Vol 11 (15) ◽  
Author(s):  
Sivarajasingham Selliah ◽  
Shri-Dewi Applanaidu
Keyword(s):  
Sri Lanka ◽  
Empirical Evidence ◽  
Food Price ◽  
Price Inflation

Extreme Events Theory and Application

2017 ◽  
pp. 83-115
Keyword(s):  
Extreme Events ◽  
Real World ◽  
Extreme Event ◽  
Investment Strategy ◽  
The Other ◽  
Price Inflation ◽  
Statistical Software ◽  
Tail Risk ◽  
Inflation Risk ◽  
World Markets

In standard statistical methodologies, the probability that the extreme event will occur is very small. But the expected losses in real world markets are higher and sometimes with catastrophic outcomes. Here it seems that the fact that we could lose a certain amount of money 95% or 99% of the time tells us absolutely nothing about what could happen the other 5 or even 1 percent of the time. For that reason, instead of estimating the certain loss, as the standard statistical methodologies account, we introduce a technique known as a “tail risk protecting strategy” or “the barbell investment strategy.” In this chapter, analyzing the copper market movements I understand that the market has been conditioned to believe that the copper demand will exceed its supply. Therefore, I suggest to protect against a growing price-inflation risk. The analyses are conducted using the statistical software STATA 11 and Excel Spreadsheets.

Food price inflation, growth and poverty

2015 ◽  
pp. 72-99
Author(s):  
Shikha Jha ◽  
P.V. Srinivasan
Keyword(s):  
Food Price ◽  
Price Inflation

Urban Wage Behaviour and Food Price Inflation in Ethiopia

2016 ◽  
Vol 53 (8) ◽  
pp. 1207-1222 ◽  
Author(s):  
Fantu Bachewe ◽  
Derek Headey
Keyword(s):  
Food Price ◽  
Price Inflation

scholarly journals Measuring food inflation during the COVID-19 pandemic in real time using online data: a case study of Poland

2021 ◽  
Vol 123 (13) ◽  
pp. 260-280
Author(s):  
Krystian Jaworski
Keyword(s):  
Real Time ◽  
Alcoholic Beverage ◽  
Food Prices ◽  
Food Price ◽  
Online Data ◽  
Price Inflation ◽  
Content Type ◽  
Price Data ◽  
Online Stores ◽  
Food Inflation

PurposeThe purpose of this study paper is to focus on developing novel ways to monitor an economy in real time during the COVID-19 pandemic. A fully automated framework is proposed for collecting and analyzing online food prices in Poland. This is important, as the COVID-19 outbreak in Europe in 2020 has led many governments to impose lockdowns that have prevented manual price data collection from food outlets. The study primarily addresses whether food price inflation can be accurately measured during the pandemic using only a laptop and Internet connection, without needing to rely on official statistics.Design/methodology/approachThe big data approach was adopted to track food price inflation in Poland. Using the web-scraping technique, daily price information about individual food and non-alcoholic beverage products sold in online stores was gathered.FindingsBased on raw online data, reliable estimates of monthly and annual food inflation were provided about 30 days before final official indexes were published.Originality/valueThis is the first paper to focus on measuring inflation in real time during the COVID-19 pandemic. Monthly and annual food price inflation are estimated in real time and updated daily, thereby improving previous forecasting solutions with weekly or monthly indicators. Using daily frequency price data deepens understanding of price developments and enables more timely detection of inflation trends, both of which are useful for policymakers and market participants. This study also provides a review of crucial issues regarding inflation that emerged during the COVID-19 pandemic.

scholarly journals DETERMINANT OF FOOD INFLATION

2018 ◽  
Vol 21 (1) ◽  
pp. 81-94
Author(s):  
Bambang Indra Ismaya ◽  
Donni Fajar Anugrah
Keyword(s):  
Empirical Finding ◽  
Food Price ◽  
Strong Impact ◽  
Price Inflation ◽  
Agriculture Sector ◽  
Rice Price ◽  
Credit Demand ◽  
General Method Of Moments ◽  
Food Inflation ◽  
Forward Looking

In this paper, we investigate the determinants of food inflation in Indonesia by applying General Method of Moments (GMM). The period of quarterly data is 2008:Q1 to 2017:Q4. The empirical finding of this study shows that backward-looking and forward-looking expectations have a strong impact on food inflation. Also, this study provided evidences that the determinants general food price inflation, such as food production, agriculture sector output, infrastructure, food import, agriculture sector credit, demand level (M1/consumption), and seasonal event (Eid Mubarak) are highly significant. Backward-looking and forward-looking expectations, domestic oil price, and level of demand have been a contributor toward high food price while the factors of general food price inflation reduce food price. In particular, we also identify the determinants of rice price inflation since it has the largest share in food price inflation. We found that backward-looking and forward-looking expectations, climate change, and demand have a strong impact on high rice price while production, productivity, harvested area, infrastructure, import, and credit reduce rice price.

scholarly journals The Effects of Rising Food and Fuel Costs on Poverty in Pakistan

2008 ◽  
Vol 13 (Special Edition) ◽  
pp. 117-138 ◽  
Author(s):  
Theresa Thompson Chaudhry ◽  
Azam Amjad Chaudhry
Keyword(s):  
Food Prices ◽  
Food Price ◽  
Energy Price ◽  
Price Shocks ◽  
Price Inflation ◽  
Fuel Prices ◽  
Price Increases ◽  
Head Count ◽  
The Impact ◽  
Poverty Levels

The dramatic increase in international food and fuel prices in recent times is a crucial issue for developing countries and the most vulnerable to these price shocks are the poorest segments of society. In countries like Pakistan, the discussion has focused on the impact of substantially higher food and fuel prices on poverty. This paper used PSLM and MICS household level data to analyze the impact of higher food and energy prices on the poverty head count and the poverty gap ratio in Pakistan. Simulated food and energy price shocks present some important results: First, the impact of food price increases on Pakistani poverty levels is substantially greater than the impact of energy price increases. Second, the impact of food price inflation on Pakistani poverty levels is significantly higher for rural populations as compared to urban populations. Finally, food price inflation can lead to significant increases in Pakistani poverty levels: For Pakistan as a whole, a 20% increase in food prices would lead to an 8% increase in the poverty head count.

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