Greek Household Energy Consumption

Socio-Economic, Demographic, and Housing Characteristics, 2004-2020

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About this dataset

This dataset provides a valuable insight into the energy consumption patterns of Greek households from 2004 to 2020. This comprehensive dataset covers an array of dimensions ranging from basic socio-economic and demographic characteristics of households, to housing characteristics and energy source data. It provides invaluable information about types of heating systems employed in homes, primary energy sources used for electricity and hot water provision, as well as average cost for these services over long periods. An analysis of this dataset can provide much needed understanding into changes in energy consumption practices over time and differences between socio-economic groups, allowing informed decisions regarding policy related to best practices with regard to energy efficiency. Do not miss out on the opportunity to understand how the current trends in household energy consumption in Greece came into existence by studying this powerful dataset!

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How to use the dataset

This dataset contains important information on the energy consumption patterns of households in Greece from 2004 to 2020. By exploring this data, we can gain insight into how energy consumption practices have changed over the period and how factors such as socio-economic and demographic characteristics, housing characteristics, and cost data have had an impact on these changes.

Here are some tips for making the best use of this dataset:

• Begin by familiarizing yourself with all the variables included in this dataset — from basic socio-economic and demographic details of households, to housing characteristics and energy source data. This understanding will ensure that you are able to make better sense of the insights received when analyzing the data.

• Use descriptive statistics such as groupby and pivot tables to analyze different trends within a variable or between variables — for example grouping by household income level or region or examining changes over time through comparison with previous years' values.

• Experiment with visualizing your findings using graphs or charts — including line graphs, histograms, scatter plots,heatmaps etc., which can help bring out more trends than just text alone could do so easily!

• Analyze cost related variables such as electricity consumption totals combined with other statistics such as average winter temperature or number of people living in a household - which may help identify key drivers impacting total energy costs for particular households over time or others alike thematically!

• Compare insights across various demographics - for example compare data about rural vs urban areas; northern vs southern regions; higher income vs lower income groups etc.; to learn broader conclusions about overall energy use among Greek households at large throughout given years/timeframes!

6Using sophisticated algorithms like linear regression models can further enhance your research results by allowing you fine tune predictions based on various inputs (such as types of fuel/ sources & annual temperatures etc), ensuring actionable results derived due to predictive decision making highly influence policy decisions related to efficiency & conservation efforts needed!

Research Ideas

• Modeling Energy Consumption Based on Socio-Economic, Demographic, and Housing Characteristics: This dataset can be used to identify the factors that influence energy consumption in Greek households. By analyzing the various demographic and housing characteristics of a given household, it may be possible to create predictive models that accurately predict energy usage for similar households in the future.
• Evaluating Changes in Energy Consumption Over Time: This dataset can also be used to observe how energy consumption patterns have changed over time. A comparison between 2004 and 2020 could provide insight into who is using more or less energy now than before and what types of changes were responsible for this shift in energy consumption habits.
• Identifying Correlations between Cost of Energy Use and Different Factors: Lastly, this dataset could help identify connections between things like cost of homes' primary sources of power, type of heating systems used, geographical region etc., and the resulting cost incurred by households when they use different kinds of energies. Coupled with further analysis such as segment...

The Greek life and non-life insurance market, while smaller than many Western European counterparts, exhibits promising growth potential. The period from 2019 to 2024 witnessed a period of recovery following the economic crisis, characterized by increased consumer confidence and a gradual rise in insurance penetration. While precise figures for market size are not provided, leveraging publicly available data on the European insurance market and considering Greece's GDP growth and population demographics, a reasonable estimation for the total market size in 2025 is approximately €8 billion, with the non-life sector slightly larger than the life sector. This is supported by the observation that non-life insurance tends to be more resilient during economic downturns due to its mandatory aspects (e.g., auto insurance). Looking forward to 2033, the compound annual growth rate (CAGR) is a crucial factor determining market expansion. Assuming a conservative CAGR of 3% based on projected Greek economic growth and increasing awareness of insurance products, the market is anticipated to reach approximately €11 billion by 2033. Growth will be driven primarily by an aging population increasing demand for health and long-term care insurance in the life sector, and rising motorization and property values boosting non-life insurance premiums. Regulatory changes aimed at improving market transparency and consumer protection will also contribute to market growth, fostering trust and encouraging greater participation. However, challenges remain; these include persistently high unemployment rates and public debt, which may temper overall market expansion. Furthermore, the industry's digital transformation will be a key driver of success, demanding investments in technology and customer-centric digital platforms. Recent developments include: In 2021, Greek Insurance Conglomerate Ethniki Sold to Private Fund. Through its subsidiaries Garanta and Ethniki Asfalistiki Cyprus, it has a significant and dynamic presence in Romania and Cyprus, respectively. Its growth has attracted the interest of several foreign funds recently. In a statement, CVC Capital announced that it has entered into a definitive agreement to acquire 90.01% of Ethniki Insurance from NBG., In 2020, Generali acquired AXA's Greek activity. The deal includes its activity in life and general insurance policies, and the tag amounts to 12.2 times the price per earnings ratio of 2019. The transaction continues the streamlining policy of the French group based on its general strategy and is expected to be completed in the second quarter of the year, pending approval by the regulatory authorities.. Notable trends are: Penetration Ratio of Insurance Premium and their Investments to GDP Increased Greece Life & Non-Life Insurance Industry Size.

Revenue is forecast to contract at a compound annual rate of 2% over the five years through 2025 to €44.7 billion. This is mostly the result of COVID-19 restrictions dampening downstream demand in 2020. While 2021 saw some recovery, poor economic conditions since 2022 have stifled any significant recovery, continuing to weigh on the industry’s revenue performance. In 2025, revenue is slated to dip by 1.1% owing to the cooling housing market, despite significant investment in civil engineering projects across Europe. Despite public funding and support for new residential properties, a weaker housing market has limited stone and aggregates demand from property developers. This is primarily the result of persistently high interest rates, inhibiting borrowing and investing. Another key factor is the decline in cement and concrete manufacturing (two key downstream markets) in Europe since 2021, according to CEMBUREAU, owing to construction companies moving towards lower embedded CO2 construction materials. Still, revenue has been propped up by growing demand from non-construction markets, like glass manufacturers, fertiliser manufacturers and other industrial and building-environment solutions applications (like sand and gravel being used to prevent coastline erosion) Over the five years through 2030, revenue is forecast to grow at a compound annual rate of 2.5%, to €50.7 billion. Economic conditions are likely to remain fairly weak in the short to medium term as inflation remains above the universal 2% target. The elevated rate of inflation will ensure central banks delay any reductions in the base rate, keeping the cost of borrowing high for would-be home buyers. Weaker demand for houses will contribute to weak price performance and disincentivise developers from increasing production, weighing on activity levels in the construction sector. However, pockets of opportunity will remain in alternative uses of stone, clay, gravel and sand.