Socioeconomic Indicators - Papua New Guinea

Income Inequality: Income inequality is a major issue in the United States and Europe, especially in large cities and between urban and rural areas. The widening gap between the wealthy and the less affluent threatens social cohesion and economic stability. Addressing this requires policies that promote more equitable economic opportunities across diverse communities.

Social Welfare Systems: Social welfare systems vary widely, particularly in Europe, where some countries have robust structures while others rely on societal self-organization. This disparity highlights the challenge of creating more uniform social protection across regions. Ensuring access to basic social services is crucial as economic inequalities persist.

Employment, Labor Productivity, and Demographic Shifts: Youth unemployment remains a pressing issue, especially in Europe, leading to long-term socioeconomic problems. Additionally, Europe faces stagnation in labor productivity, with recent increases mostly driven by inflation rather than genuine productivity improvements. Aging populations in Europe and parts of Asia further strain pension systems and healthcare, requiring policies that adapt to these demographic shifts and better integrate younger workers.

Poverty Reduction and Sustainable Development: While progress in reducing poverty has been made in Asia, challenges remain in ensuring sustainable and inclusive growth. Rural areas‘ structural weakness creates disparities of opportunity that hinder equitable development. Achieving sustainable growth that benefits all is essential for long-term stability.

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.