Consumption Indicators - Norway

  • Norway
  • In 2024, the household disposable income in Norway is forecast to amount to US$276.80bn.
  • In 2024, the household disposable income per capita in Norway is forecast to amount to US$50.20k.
  • The total consumer spending in Norway is forecast to amount to US$163.40bn in 2024.
  • The consumer spending per capita on food and non-alcoholic beverages in Norway is forecast to amount to US$3.40k in 2024.
  • The consumer spending per capita on housing in Norway is forecast to amount US$6.85k in 2024.
  • The consumer spending per capita on healthcare in Norway is forecast to amount US$0.96k in 2024.
  • The clothing and footwear consumer spending per capita in Norway are forecast to amount to US$1.43k in 2024.
  • The consumer spending per capita on the household in Norway is forecast to amount US$1.89k in 2024.
  • The consumer spending per capita on miscellaneous goods in Norway is forecast to amount US$2.97k in 2024.
  • In 2024, the estimated consumer spending per capita on culture and recreation in Norway is US$3.57k.
  • The consumer spending per capita in hospitality and restaurants sector in Norway is forecast to amount US$2.10k in 2024.
  • The consumer spending per capita on alcohol in Norway is forecast to amount US$1.14k in 2024.
  • The consumer spending on education in Norway is estimated to amount US$136.80 in 2024.
  • The consumer spending per capita in communication in Norway is forecast to amount US$0.60k in 2024.
  • The consumer spending per capita on transport in Norway is forecast to amount US$4.59k in 2024.
 
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Analyst Opinion

The consumption indicators provide key insights into economic health and individual purchasing behavior. Consumer spending is a key driver of economic growth and serves as an important measure of overall economic activity. Various sectors, from food and housing to healthcare and education, contribute to these indicators and reflect the wide range of goods and services to which individuals allocate their spending. Tracking these indicators allows policymakers, businesses, and economists to monitor trends, assess market conditions, and make informed decisions about resource allocation, market strategies, and economic policies. However, the consumption indicators domain faces challenges influenced by regulatory factors and ongoing trends, including the rise of e-commerce, sustainable consumption, the desire for personalized experiences, and technological advances. Effectively addressing these challenges is critical for stakeholders to align their strategies with evolving consumer preferences and market dynamics.

Methodology

Data coverage:

The dataset encompasses data from 152 countries. The charts depict the situation of each country in six different domains. These domains are socioeconomic indicators, macroeconomic indicators, health indicators, digital and connectivity indicators, consumption indicators, as well as logistics and transport indicators. Within these domains, various segments are covered, including demography, economic measures, economic inequality, employment, consumption, health determinants, and much more.

Modeling approach:

The composition of each domain follows a comprehensive approach that combines both top-down and bottom-up methodologies, with each domain and segment being guided by a specific rationale. To evaluate the situation of these six domains within each country, we rely on pertinent indicators and data from reputable international institutions, local national statistical offices, industry associations, and leading private institutions. Additionally, we undertake data processing procedures to address issues such as missing timelines, outliers, and data inconsistency. Our data processing incorporates advanced statistical techniques, including interpolation, exponential moving weighted average, and the Savitzky-Golay filter. These methods contribute to the refinement and enhancement of data quality.

Forecasts:

In our forecasting process, a wide range of statistical techniques is utilized based on the characteristics of the markets. For example, the S-curve function is employed to forecast the adoption of new technology, products, and services, aligning the forecast model with the theory of innovation adoption. Additionally, the data is forecasted using ARIMA with and without seasonality considerations, exponential trend smoothing, and the Compound Annual Growth Rate (CAGR), with the option to incorporate adjustment factors when necessary. These techniques enable accurate and reliable forecast methods tailored to the unique characteristics of the data in each market and country.

Additional notes:

The data is updated twice per year or every time there is a significant change in their dynamics. The impacts of the COVID-19 pandemic and of the Russia/Ukraine war are considered at a country-specific level.

Overview

  • Household Income
  • Household Expenditure
  • Analyst Opinion
  • Methodology
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