Longitudinal Data
What Is Longitudinal Data?
Longitudinal data, sometimes called panel data, will be data that is collected through a series of rehashed perceptions of similar subjects throughout some extended time period — and is valuable for measuring change. Longitudinal data effectively follows a similar sample after some time, which contrasts fundamentally from cross-sectional data in light of the fact that it follows similar subjects throughout some time, while cross-sectional data samples various subjects (whether individuals, firms, countries, or locales) at each point in time. In the mean time, a cross-sectional data set will continuously draw another [random sample](/basic random-sample).
Longitudinal data is utilized widely in the social sciences, including among financial specialists, political researchers, and sociologists.
Figuring out Longitudinal Data
Frequently, analysts are keen on how things change over the long haul. In a common cross-sectional sample, even on the off chance that you measure some variable today and, again in twelve months, you will likely be sampling various individuals each time. To understand how things change for similar individuals after some time, you should have the option to follow them and follow up with them in about a year, and in later waves. This is longitudinal data.
Longitudinal data is many times utilized in economic and financial studies since it enjoys several upper hands over rehashed cross-sectional data. For instance, in light of the fact that longitudinal data measures how long events last, it very well may be utilized to check whether similar group of individuals stay jobless during a recession, or whether various individuals are moving all through unemployment. This can assist with deciding the factors that most influence unemployment.
Applications of Longitudinal Data
Longitudinal analysis can likewise be utilized to compute a portfolio's value at risk (VaR), utilizing the historic simulation method. This reproduces how the value of the current portfolio would have vacillated throughout previous time spans, involving the noticed historical variances of the assets in the portfolio during those times. It gives an estimate of the maximum likely loss throughout the next time span.
Longitudinal data is likewise utilized in event studies to dissect what factors drive abnormal stock returns over the long run, or how stock prices respond to merger and earnings declarations. It can likewise be utilized to measure poverty and income inequality by tracking individual families. What's more, on the grounds that state sanctioned test scores in schools are longitudinal, they can be utilized to evaluate teacher effectiveness and different factors influencing student performance.
Social researchers likewise utilize longitudinal data to try to comprehend causation of events that might have happened in the past and how they lead to results saw in later waves of the data. For example, the effect of the entry another law on crime statistics, or a natural disaster on births and passings years after the fact.
Features
- Longitudinal data will be data that is collected successively from similar respondents after some time.
- This type of data can be vital in tracking trends and changes over the long haul by asking similar respondents inquiries in several waves carried in a tough spot.
- Longitudinal data is utilized in finance to follow company profitability, risk, and to grasp the effect of economic shocks.
