Background
A quota sample is a type of non-probability sampling method where the researcher ensures that specific characteristics of the population are represented in the sample. This means that while members of different sections of the population are sampled in fixed proportions, these proportions do not necessarily reflect those of the overall population. This technique is destined to ensure that certain groups are included in the sample, facilitating more thorough data analysis of those groups.
Historical Context
Quota sampling has its roots in early 20th-century social research. Pioneers in market research and social sciences utilized quota sampling as a cost-effective and convenient alternative to probability sampling, which sometimes required extensive resources.
Definitions and Concepts
- Quota Sample: A non-random sample for which the researcher has specified the exact proportions of various demographic characteristics (e.g., age, sex, income level) to be included.
Important elements include:
- Selecting specific demographic proportions
- Intentional inclusion of particular subgroups
Major Analytical Frameworks
Classical Economics
Classical economists didn’t focus extensively on statistical sampling methods, yet the representation of diverse population segments aligns philosophically with classical methods to understand the workings of different economic agents.
Neoclassical Economics
In neoclassical economics, the theory of utility and consumer preference can be examined using quota samples to gather detailed data on attitudes, which might be essential for granular economic behavior analysis.
Keynesian Economics
Ideally suited for examining the behavior of different economic strata under varying fiscal policies, quota sampling can help identify the efficacy of various interventions aimed at market stabilization.
Marxian Economics
Quota samples may be used to represent the distinct interests and conditions of different classes. This sampling method aligns with Marxist analysis focused on how socioeconomic classes experience economic phenomena differently.
Institutional Economics
Quota sampling could be used to explore how different groups interact with and are affected by institutional structures, including laws, norms, and regulations.
Behavioral Economics
Quota samples are particularly useful in behavioral economics to ensure that sample compositions capture nuanced differences in decision-making across demographic groups.
Post-Keynesian Economics
This subfield, with its focus on heterodox approaches, benefits from quota sampling to delve deeply into specific, underrepresented population dynamics influencing broader economic outcomes.
Austrian Economics
Although Austrian economists often emphasize qualitative methods over quantitative approaches like sampling, quota samples can provide meaningful data on entrepreneurial activities among different demographic groups.
Development Economics
In development economics, quota sampling helps highlight issues and conditions affecting various sectors of the population, particularly in regions with significant socio-economic diversity.
Monetarism
Quota sampling assists monetarists in understanding how different financial policies and inflation rates impact diverse demographic groups within a population.
Comparative Analysis
- Quota Sample vs. Random Sample: Random sampling aims for true randomness, which means every individual has an equal chance of being selected. Quota sampling, on the other hand, intentionally includes pre-specified numbers of subgroups.
- Quota Sample vs. Stratified Sample: Stratified random sampling also involves dividing the population into subgroups, but within each subgroup, participants are randomly selected, which increases representativeness compared to non-probability based quota sampling.
Case Studies
Quota samples are often used in:
- Market research surveys for targeted demographics
- Public opinion polls ensuring representation from various demographic groups
- Sociological studies examining underrepresented or marginalized populations
Suggested Books for Further Studies
- Social Science Research: Principles, Methods, and Practices by Anol Bhattacherjee
- Survey Methodology by Robert M. Groves et al.
- Research Design: Qualitative, Quantitative, and Mixed Methods Approaches by John W. Creswell
Related Terms with Definitions
- Random Sample: A sampling method where every individual has an equal chance of being selected, ensuring the selection is representative of the whole population.
- Stratified Sample: A probability sampling method where the population is divided into subgroups (strata), and random samples are taken from each strata.
- Convenience Sample: A non-probability sample where participants are selected based on their availability or ease of access.
