How does firm experience and institutional distance impact ownership choice in high‐technology acquisitions?

One of the critical reasons for a firm to acquire other firms is to access new technology. This study seeks to understand what ownership position a firm should take in foreign markets if the target is in a high‐technology industry. Specifically, it looks at how firm‐level experience and institutional distance could impact this ownership. Using logistic regression models on a sample of 1,091 cross‐border acquisitions undertaken by firms from 36 countries over an 8‐year time period (2001–2008), we find that when firms acquire targets in a high‐technology industry, they resort to partial acquisitions. Our analysis further suggests that when firms seek targets in high‐technology industries but have experience with acquisitions or face higher institutional distance, the likelihood of full acquisitions over partial ones increases. Study findings contribute to our understanding of the interactive relationship among technology, experience, and institutional distance in determining appropriate ownership choices.     

Tax competition with asymmetric market structures: The role of policy instruments*

We analyze the location choice of a multinational corporation (MNC) between two host countries with different market structures, i.e. the number of competing domestic firms in them. We consider the effects of import tariffs and lump-sum subsidies on the MNC's locational choice. Our findings include: (1) with lump-sum subsidy, the country with fewer firms always gets the MNC, (2) with tariffs, the country with more domestic firms gets the MNC when the export transportation cost is high and the domestic firms are sufficiently inefficient, while the country with fewer domestic firms wins the MNC when export transportation cost is low, and (3) the MNC location decision may crucially depend on which instrument is used to attract the MNC.     

Competition for foreign direct investment: The role of technology and market structure

We analyze the location choice of a multinational corporation (MNC) between two host countries. We consider both passive and active governments and examine the role of production efficiencies, and of market structure, in the MNC's choice. Our findings include: (i) when the domestic firms export, the country with fewer firms always gets the MNC, but the MNC is indifferent between hosts with firms that have different efficiency levels, (ii) when the domestic firms do not export, the country with more firms gets the MNC if they are sufficiently inefficient, and the MNC locates in the country with less efficient firms.     

Lobbying by Ethnic Groups and Aid Allocation

We develop a political-economic model of foreign aid allocation. Each ethnic group in the donor country lobbies the government to allocate more aid to its country of origin, and the government accepts political contributions from lobby groups. Initial per-capita income of the recipients and those of the ethnic groups are shown to be important determinants of the solution of the political equilibrium. We also examine the effects of changes in the degree of corruption, aid fatigue, and ethnic composition, in the donor country on the allocation of aid.     

Quantitative restrictions and Indian imports

Many governments in LDCs tend 3o rely heavily on import control for achieving adjustments in the balance of payments. The empirical analysis of imports of these countries has failed to address the issue of quantitative restrictions satisfactorily. In this paper, a set of disaggregated import demand equations are specified which attempt to capture the government's decision regarding quota restrictions. The model postulates that the overall level of imports is determined by expected foreign exchange availability while the composition of imports (once the level has been decided) is based on political and economic priorities and on relative prices.     

On reconciling purchases and sales estimates of a regional input-output table

This paper develops two alternative methods for reconciling purchases and sales estimates of a regional input-output table. The present procedures are extentions of the well known Jensen-McGaurr (J-M) procedures. It is claimed that the proposed techniques would reduce to a great extent the subjective elements in the J-M procedure and thus lower the time costs to the researcher. The present methods have been applied to the data for the Central Queensland Economy and comparisons made between the results coming out of the present procedures and the J-M procedure. In particular, it has been found that the present procedures, though less subjective in nature, produce estimates that are as reliable as the J-M estimates.     

A model of Social Security Disability Insurance using matched SIPP/Administrative data

We study Disability Insurance (DI) application behavior in the US using matched SIPP and administrative data over 1989–1995. Certain state-contingent earnings projections and eligibility probabilities are central to the analysis. We find evidence for a small work disincentive effect of DI that seems to be restricted to a subset of the DI beneficiaries, including low earning groups such as blue collar workers and those subject to economic dislocation. Processing time, Medicare value, unemployment, private health insurance, and health shocks are some of the major factors that affect application propensity. The behavioral response of female workers to various parameters of the DI program is found to be quite different from that of males.     

Short–run electricity demand forecasts in Maharashtra

This paper, has tried to forecast monthly maximum electricity demand for the state Maharashtra, India, using Multiplicative Seasonal Autoregressive Integrated Moving Average (MSARIMA) method for seasonally unadjusted monthly data spanning from April 1980 to June 1999. The forecasted period is 18 months ahead from June 1999. This study's basic findings are that the series does not reveal any drastic change for the forecasted period. It continues to follow the same trend along with the seasonal variation.     

Statistical Analysis with Linked Data

Computerised Record Linkage methods help us combine multiple data sets from different sources when a single data set with all necessary information is unavailable or when data collection on additional variables is time consuming and extremely costly. Linkage errors are inevitable in the linked data set because of the unavailability of error‐free unique identifiers. A small amount of linkage errors can lead to substantial bias and increased variability in estimating parameters of a statistical model. In this paper, we propose a unified theory for statistical analysis with linked data. Our proposed method, unlike the ones available for secondary data analysis of linked data, exploits record linkage process data as an alternative to taking a costly sample to evaluate error rates from the record linkage procedure. A jackknife method is introduced to estimate bias, covariance matrix and mean squared error of our proposed estimators. Simulation results are presented to evaluate the performance of the proposed estimators that account for linkage errors.