The growth impact of the metropolitan statistical area designation

2007 ◽  
Vol 42 (2) ◽  
pp. 307-319 ◽  
Author(s):  
George W. Hammond ◽  
Brian J. Osoba
Keyword(s):  
Metropolitan Statistical Area ◽  
Statistical Area

scholarly journals Lagged Associations of Metropolitan Statistical Area- and State-Level Income Inequality with Cognitive Function: The Health and Retirement Study

PLoS ONE ◽  
2016 ◽  
Vol 11 (6) ◽  
pp. e0157327 ◽  
Author(s):  
Daniel Kim ◽  
Beth Ann Griffin ◽  
Mohammed Kabeto ◽  
José Escarce ◽  
Kenneth M. Langa ◽  
...  
Keyword(s):  
Cognitive Function ◽  
Income Inequality ◽  
State Level ◽  
Health And Retirement Study ◽  
Metropolitan Statistical Area ◽  
Retirement Study ◽  
Statistical Area

scholarly journals Airport Choice Modeling: Empirical Evidence from a Non-Hub Airport

2012 ◽  
Vol 50 (2) ◽  
Author(s):  
Steve Leon
Keyword(s):  
Binary Logistic Regression ◽  
Choice Modeling ◽  
Metropolitan Statistical Area ◽  
Comprehensive Review ◽  
Travel Agents ◽  
Trip Purpose ◽  
Hub Airport ◽  
Statistical Area ◽  
Passenger Choice ◽  
Significant Factors

A comprehensive review of airport choice modeling studies is presented in this paper, highlighting the key determinants of passenger preferences. Empirical research presented which models using binary logistic regression in the likelihood that airline travelers in the Fargo-Moorhead Metropolitan Statistical Area will not use the local airport, but instead use the competing major hub airport in Minneapolis-St. Paul, located 250 miles away as a viable origin airport. Moreover, this study investigates whether collecting empirical data from local travel agents may perhaps allow airport planners and airport managers to identify important passenger choice behaviors without incurring the added time and expense of administering formal passenger surveys. This study found that it is possible to obtain useful data from travel agents at significantly less time and effort. The significant factors obtained from the regression analysis were trip purpose, trip duration, number of connections, and airline.

scholarly journals ARE HOUSING PRICE CYCLES ASYMMETRIC? EVIDENCE FROM THE US STATES AND METROPOLITAN AREAS

2018 ◽  
Vol 23 (1) ◽  
pp. 1-22 ◽  
Author(s):  
Christophe André ◽  
Rangan Gupta ◽  
John W. Muteba Mwamba
Keyword(s):  
Loss Aversion ◽  
Linear Models ◽  
Metropolitan Areas ◽  
Housing Prices ◽  
District Of Columbia ◽  
Housing Price ◽  
Metropolitan Statistical Area ◽  
The Us ◽  
Housing Price Dynamics ◽  
Statistical Area

This paper investigates asymmetry in US housing price cycles at the state and metropolitan statistical area (MSA) level, using the Triples test (Randles, Flinger, Policello, & Wolfe, 1980) and the Entropy test of Racine and Maasoumi (2007). Several reasons may account for asymmetry in housing prices, including non-linearity in their determinants and in behavioural responses, in particular linked to equity constraints and loss aversion. However, few studies have formally tested the symmetry of housing price cycles. We find that housing prices are asymmetric in the vast majority of cases. Taking into account the results of the two tests, deepness asymmetry, which represents differences in the magnitude of upswings and downturns, is found in 39 out of the 51 states (including the District of Columbia) and 238 out of the 381 MSAs. Steepness asymmetry, which measures differences in the speed of price changes during upswings and downturns, is found in 40 states and 257 MSAs. These results imply that linear models are in most cases insufficient to capture housing price dynamics.

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