Censored Sample

Definition and meaning of censored sample in economics.

Background

In statistical and econometric analysis, datasets are frequently encountered which exhibit censored observations. A censored sample contains data where the value of interest (the dependent variable) gets truncated because it falls outside a certain range, even though the influencing factors (independent variables) are known.

Historical Context

The concept of censored samples gained traction with the development of econometric models capable of handling such anomalies. Originally, the legibility of censored samples drew upon applied econometricians who sought reliable ways to estimate demand, revenue models, and other vital statistical figures affected by such truncations.

Definitions and Concepts

Censored Sample

A censored sample arises when the observations of the dependent variable are either wholly or partially uninterrupted because of them lying outside certain threshold bounds defined by independent variables. For example:

  • Measuring demand for concert tickets in a hall becomes tricky if one only knows the sales till the tickets are sold out; thus creating a censoring problem.

Censoring can be:

  • Left-censored: where an observation below a certain threshold is not observed.
  • Right-censored: where an observation above a certain threshold is undetected.

Major Analytical Frameworks

Classical Economics

Classical economics does not inherently consider censored samples due to its foundational focus on macroeconomic principles without granular data irregularities.

Neoclassical Economics

Neoclassical economics, which refines microeconomic fundamentals through utility maximization, may encounter such samples in practical evaluations, necessitating robust handling mechanisms.

Keynesian Economic

Keynesian models focusing on aggregate demand and supply typically overlook censored data, though refined models may still consider censored financial or consumption behavior.

Marxian Economics

Marxian economics largely concerns macrohistoric perspectives, so direct applicability of censored samples is limited unless discussing macroaggregations in a capitalistic system.

Institutional Economics

Institutional economics considers the role of structures and social norms, which can experience censored phenomenological data in auditing macroeconomic behavior.

Behavioral Economics

Behavioral economics scrutinizes individual decision-making, often encountering censored datasets, necessitating specialized models to comprehend true behavioral extents.

Post-Keynesian Economics

Post-Keynesian focuses on real economies and may analyze censored data in financial models emphasizing market imperfections and investment adjustments.

Austrian Economics

While Austrian economics emphasizes qualitative insights and individual actions, acknowledging censored samples can refine precision in spontaneous market orders research.

Development Economics

Development economists frequently encounter censored samples in emerging markets with data issues like truncated income proofs or censored health outcome corpus.

Monetarism

Monetarists seeking to quantify policy impact on money flow may interpret censored datasets within monetary aggregates or transactional discrepancies.

Comparative Analysis

Different schools offer mechanisms to handle censored samples. For instance, classical methods may deploy omission strategies, whilst modern techniques might introduce sophisticated models such as Tobit regression― methodologically understanding the latent variable/readily constrained data concept.

Case Studies

  • Concert Tickets Sales: Demands estimation from sales data where frequent sell-outs result in highly censored observed data.
  • Income Reporting in Surveys: Instances where top incomes aren’t captured above certain anonymized thresholds.

Suggested Books for Further Studies

  • “Analysis of Censored and Truncated EB Data” by Lee-Ann C. Hayek
  • “Understanding Econometrics: An Empirical Approach” by Mehmet Ugur and Ranjeeta Thomas
  • Tobit Model: Statistical model proposed by James Tobin (1958) used for estimating linear relationships where dependent variable is censored.
  • Truncated Sample: A type of incomplete sampling where observations falling outside a specified range get entirely excluded.
  • Selection Bias: Bias introduced when a non-random sample unrepresentatively reflects population variances.
Wednesday, July 31, 2024