Panel Data

The following is a panel of data on investment (y) and profit (x) for n=3 firms over 7M0 periods. 

The fixed effects regression can be computed just by including the three dummy variables since the sample sizes are quite small. The results are 

The critical value from the F table is 19.458, so the hypothesis is not rejected. 

In order to estimate the random effects model, we need some additional parameter estimates. The group means are y x 

In the group means regression using these three observations, we obtain yi = 10.665 +. 29909, . with e e =. 19747. 

---

More and more commonly, fire alarm panel data is transferred to a safety instrumented system (SIS) for graphic annunciation though the SIS human-machine interface (HMI). 

Expansion of the government s role is likely to crowd out private investment. Lichtenberg (1984) provides estimates of the relationship between company and federal R D, based on data compiled by the National Science Foundation for the period 1967-1977. The availability of firm-level panel data on both R D expenditure and employment permitted investigation... 

Using the above measures for pharmaceutical innovation and health outcomes, we constructed panel data for disease-specific health outcomes and the cumulative number ofNMEs for each disease category. We hypothesized that diseases associated with a higher rate of pharmaceutical innovations would experience greater improvements in health outcomes. 

Table 13.2. Regression results in panel data models...

Branstetter, Lee G., Raymond Fisman, and C. Fritz Foley. 2003. Do Stronger Intellectual Property Rights Increase International Technology Transfer Empirical Evidence from U.S. Firm-Level Panel Data. Unpublished paper, Columbia University Business School. 

Lancaster T, Intrator O. Panel data with survival hospitalization of HIV patients. Brown University Department of Economics Working Paper Series, 95-36 1995. 

Recent developments In microcomputers, sensory analysis and experimental design have made it possible to efficiently evaluate and optimize products. This paper focuses on the conduct and analysis of a study to optimize the flavor constituents of an alcoholic "digestive" liqueur. It illustrates the use of the panel data, and the contributions of the microcomputer as both a tool for gathering data, and as an inexpensive replacement for mainframe computers in statistical computations. 

In the panel data models estimated in Example 21.5.1, neither the logit nor the probit model provides a framework for applying a Hausman test to determine whether fixed or random effects is preferred. Explain. (Hint Unlike our application in the linear model, the incidental parameters problem persists here.) Look at the two cases. Neither case has an estimator which is consistent in both cases. In both cases, the unconditional fixed effects effects estimator is inconsistent, so the rest of the analysis falls apart. This is the incidental parameters problem at work. Note that the fixed effects estimator is inconsistent because in both models, the estimator of the constant terms is a function of 1/T. Certainly in both cases, if the fixed effects model is appropriate, then the random effects estimator is inconsistent, whereas if the random effects model is appropriate, the maximum likelihood random effects estimator is both consistent and efficient. Thus, in this instance, the random effects satisfies the requirements of the test. In fact, there does exist a consistent estimator for the logit model with fixed effects - see the text. However, this estimator must be based on a restricted sample observations with the sum of the ys equal to zero or T muust be discarded, so the mechanics of the Hausman test are problematic. This does not fall into the template of computations for the Hausman test. 

Since several studies identified the aliphatic and heterocyclic sulfur compounds as being important to cooked-beef flavor (9-11). the present report focuses upon a few key sulfur compounds that contribute to flavor of cooked meat as they change with time and temperature. Previous work has been directed to obtaining reliable correlation of sensory panel data with objective instrumental data describing meat flavor deterioration on storage (1). The present study is targeted toward obtaining a reliable, objective assay... 

Figure 7.44. Effects of temperature on release of quanta of acetylcholine (ACh) at the neuromuscular junction of the extraocular nerve of the Antarctic fish Pagothenia borchgrevinki (upper panel data from Macdonald et al., 1988), and on binding of acetylcholine to acetylcholine esterases of several marine fishes (lower panel data from Baldwin, 1971.)...

Furthermore, the new sensory method avoids several problems inherent in the Scoville procedure. Heat build up, fatigue, and increased threshold are minimized by use of a standardized initial sample, as well as timed rinsing between samples. Ethanol bite is avoided by use of an aqueous extraction. The panel data may be manipulated statistically due to the linearity of the scale and the number of panelists. Reference standards are included. Extraction time is reduced from 16 hours to 20 minutes. Reproducibility of results has been demonstrated. The error of central tendency is avoided by not having a "middle sample. The new method is more comparable to normal food usage as it is an aqueous rather than ethanol extraction. 

Each specification should contain the following panel data ... 

Figure 18.7 Salinity versus concentration plots for NO2 + NO3 during dry, average and wet years in the Patuxent River estuary. Summer and winter values are shown in each panel. Data were from the Chesapeake Bay Water Quality Monitoring Program (2004).

Figure 8. Renaturation of low molecular weight urokinase observed in samples collected from continuous flow refolding. UK was injected in 9.3 M urea into 2.0 M urea, 20 mM Bis-Tris, pH 7.8 buffer with a gradient from 2.5 mM reduced glut-athione (GSH) to 2.5 mM oxidized glutathione (GSSG). Upper panel Data for GSSG concen-tration are from direct absorbance measurements at the secondary UV detector data for GSH were determined by DTNB titration of collected fractions. Lower panel urokinase activity in collected fractions measured by spectrophotometric assay using S-2444 (12) in a Molecular Devices titerplate reader.

Figure 2. Effect of various treatments on cardiac index (upper panel) and pulmonary vascular resistance (lower panel). Data adapted from (140).

Chromium(lll) is the archetypal d ion and the electronic spectra and magnetic properties of its complexes have therefore been exhaustively studied (see Panel). Data for a representative sample of complexes are given in Table 23.6. 

Figure 4.37. Time-resolved fluorescence anisotropy of d(CGG[AP]GGC) and complement, with a G across from AP. (T< ) Residual of difference between anisotropy data and best-fit curve. (Middle) The upper curve is the polarized intensity decay of emission parallel to the excitation source s polarization the lower curve is the polarized intensity decay of emission perpendicular to the excitation source s polarization. (Bottom) Anisotropy decay calculated from the middle panel data. [From Fig. 4 of Ref. 340, with permission.]...

---