John Conlisk
Biographic Data
| ID | 331610 |
|---|---|
| NAME | John Conlisk |
| GIVEN NAMES | John |
| FAMILY NAME | Conlisk |
| SIGNATURE | CONLISK J |
| AFFILIATIONS | University of California San Diego |
| VERIFIED | No |
| TOTAL WORKS | 15 |
| TOTAL CITATIONS | 43 |
| AUTHOR COUNT | 15 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1966 |
| LATEST PUBLICATION YEAR | 2003 |
| H-INDEX | 3 |
A Note on Convergence of Adaptive Satisficing to Optimal Stopping
The model concerns a searcher making multiple searches from the same distribution of payoffs. The searcher does not know the distribution, does not attempt to infer it from cumulating information, and does not attempt to compute an optimal stopping rule. Instead the searcher follows thoroughly elementary adaptive rules. Nonetheless, the searcher converges to optimal stopping
Actions influenced by a social network
Imitation and the dynamics of norms
Dynamics of imitation
In the model, each person in a large population chooses between two options, such as adhering to or not adhering to a social norm. People observe each others’ choices at random and adjust their adherence probabilities in imitative directions. It is known from earlier work that, under strong restrictions on the imitation, the distribution of adherence probabilities will either evolve upward toward a high adherence equilibrium or downward toward a …
Stability and monotonicity for interactive Markov chains
In a Markov chain model of a social process, interest often centers on the distribution of the population by state. One question, the stability question, is whether this distribution converges to an equilibrium value. For an ordinary Markov chain (a chain with constant transition probabilities), complete answers are available. For an interactive Markov chain (a chain which allows the transition probabilities governing each individual to depend on…
Monotone mobility matrices
The transition matrix of a discrete Markov chain is called monotone if each row stochastically dominates the row above it. Monotonicity is an ideal assumption to impose on a Markov chain model of mobility. Monotonicity is behaviorally weak yet mathematically strong. It is behaviorally weak in the sense that it is theoretically plausible and is empirically supported. It is mathematically strong in the sense that monotone Markov chains have a numbe…
Eigenvalue immobility measures for Markov chains 1
Two eigenvalue measures of immobility are proposed for social processes described by a Markov chain. One is the second largest eigenvalue modulus of the chain's transition matrix. The other is the second largest eigenvalue modulus of a closely related transition matrix. The two eigenvalue measures are compared to each other and to correlation and regression‐to‐the‐mean measures. In illustrative applications to intergenerational occupational mobil…
Eigenvector Status Proxies in Markov Chain Mobility Models
In Markov chain studies of occupational mobility, an interesting empirical pattern has been reported. Certain transrtion matrix eigenvectors provide surprisingly accurate proxies for occupational status. Through a number of formal illustra tions, this paper suggests why the pattern might in theory be expected, in the occupational mobility context and in other mobility contexts
A stability theorem for an interactive Markov chain
Interactive markov chains
Markov chains, and various generalizations of them, almost universally assume that the transition probabilities applying to a single individual are independent of the behavior of other individuals in the population. That is, there is no interaction among individuals. This is an extremely limiting assumption in modelling social processes. This paper concerns interactive Markov chains, defined as Markov chains in which transition probabilities are …
Quick Stability Checks and Matrix Norms
Consider the difference equation system yt=b+Ayt-i; where yt is an nXl variable vector, b is an nXl constant vector and A is an nXn constant matrix. The fundamental necessary and sufficient stability condition for the system is /x(^)< 1, where [J.(A) is the modulus of the characteristic root of A of largest modulus. That is, IJ.(A) is the spectral radius of A, so-called because all roots of A lie on or within a circle of radius ix(A) in the compl…
Allocating foreign aid
A Neoclassical Growth Model with Endogenously Positioned Technical Change Frontier
Journal Article A Neoclassical Growth Model with Endogenously Positioned Technical Change Frontier Get access John Conlisk John Conlisk University of California, San Diego. Search for other works by this author on: Oxford Academic Google Scholar The Economic Journal, Volume 79, Issue 314, 1 June 1969, Pages 348–362, https://doi.org/10.2307/2230173 Published: 01 June 1969
Some Cross-State Evidence on Income Inequality
such investors can be dichotomized into two steps.'6 First the investor picks the optimal ratios of risky securities in his portfolio. Then, he decides on the optimal amounts of this composite risky security and the certain security. latter problem is just like that already studied by Arrow,17 so it is known that in this case all the risky securities will be inferior or superior 18 as U/U' increases or decreases with increasing wealth. When the u…
Unemployment in a Neoclassical Growth Model
Journal Article Unemployment in a Neoclassical Growth Model: The Effect on Speed of Adjustment Get access John Conlisk John Conlisk Rice University, Houston, Texas. Search for other works by this author on: Oxford Academic Google Scholar The Economic Journal, Volume 76, Issue 303, 1 September 1966, Pages 550–566, https://doi.org/10.2307/2229521 Published: 01 September 1966
Interactive markov chains
Markov chains, and various generalizations of them, almost universally assume that the transition probabilities applying to a single individual are independent of the behavior of other individuals in the population. That is, there is no interaction among individuals. This is an extremely limiting assumption in modelling social processes. This paper concerns interactive Markov chains, defined as Markov chains in which transition probabilities are …
Eigenvalue immobility measures for Markov chains 1
Two eigenvalue measures of immobility are proposed for social processes described by a Markov chain. One is the second largest eigenvalue modulus of the chain's transition matrix. The other is the second largest eigenvalue modulus of a closely related transition matrix. The two eigenvalue measures are compared to each other and to correlation and regression‐to‐the‐mean measures. In illustrative applications to intergenerational occupational mobil…
A stability theorem for an interactive Markov chain
A Neoclassical Growth Model with Endogenously Positioned Technical Change Frontier
Journal Article A Neoclassical Growth Model with Endogenously Positioned Technical Change Frontier Get access John Conlisk John Conlisk University of California, San Diego. Search for other works by this author on: Oxford Academic Google Scholar The Economic Journal, Volume 79, Issue 314, 1 June 1969, Pages 348–362, https://doi.org/10.2307/2230173 Published: 01 June 1969
Monotone mobility matrices
The transition matrix of a discrete Markov chain is called monotone if each row stochastically dominates the row above it. Monotonicity is an ideal assumption to impose on a Markov chain model of mobility. Monotonicity is behaviorally weak yet mathematically strong. It is behaviorally weak in the sense that it is theoretically plausible and is empirically supported. It is mathematically strong in the sense that monotone Markov chains have a numbe…
A Note on Convergence of Adaptive Satisficing to Optimal Stopping
The model concerns a searcher making multiple searches from the same distribution of payoffs. The searcher does not know the distribution, does not attempt to infer it from cumulating information, and does not attempt to compute an optimal stopping rule. Instead the searcher follows thoroughly elementary adaptive rules. Nonetheless, the searcher converges to optimal stopping
Stability and monotonicity for interactive Markov chains
In a Markov chain model of a social process, interest often centers on the distribution of the population by state. One question, the stability question, is whether this distribution converges to an equilibrium value. For an ordinary Markov chain (a chain with constant transition probabilities), complete answers are available. For an interactive Markov chain (a chain which allows the transition probabilities governing each individual to depend on…
Eigenvector Status Proxies in Markov Chain Mobility Models
In Markov chain studies of occupational mobility, an interesting empirical pattern has been reported. Certain transrtion matrix eigenvectors provide surprisingly accurate proxies for occupational status. Through a number of formal illustra tions, this paper suggests why the pattern might in theory be expected, in the occupational mobility context and in other mobility contexts
Quick Stability Checks and Matrix Norms
Consider the difference equation system yt=b+Ayt-i; where yt is an nXl variable vector, b is an nXl constant vector and A is an nXn constant matrix. The fundamental necessary and sufficient stability condition for the system is /x(^)< 1, where [J.(A) is the modulus of the characteristic root of A of largest modulus. That is, IJ.(A) is the spectral radius of A, so-called because all roots of A lie on or within a circle of radius ix(A) in the compl…
Unemployment in a Neoclassical Growth Model
Journal Article Unemployment in a Neoclassical Growth Model: The Effect on Speed of Adjustment Get access John Conlisk John Conlisk Rice University, Houston, Texas. Search for other works by this author on: Oxford Academic Google Scholar The Economic Journal, Volume 76, Issue 303, 1 September 1966, Pages 550–566, https://doi.org/10.2307/2229521 Published: 01 September 1966
Unemployment in a Neoclassical Growth Model
Journal Article Unemployment in a Neoclassical Growth Model: The Effect on Speed of Adjustment Get access John Conlisk John Conlisk Rice University, Houston, Texas. Search for other works by this author on: Oxford Academic Google Scholar The Economic Journal, Volume 76, Issue 303, 1 September 1966, Pages 550–566, https://doi.org/10.2307/2229521 Published: 01 September 1966
Some Cross-State Evidence on Income Inequality
such investors can be dichotomized into two steps.'6 First the investor picks the optimal ratios of risky securities in his portfolio. Then, he decides on the optimal amounts of this composite risky security and the certain security. latter problem is just like that already studied by Arrow,17 so it is known that in this case all the risky securities will be inferior or superior 18 as U/U' increases or decreases with increasing wealth. When the u…
Allocating foreign aid
A Neoclassical Growth Model with Endogenously Positioned Technical Change Frontier
Journal Article A Neoclassical Growth Model with Endogenously Positioned Technical Change Frontier Get access John Conlisk John Conlisk University of California, San Diego. Search for other works by this author on: Oxford Academic Google Scholar The Economic Journal, Volume 79, Issue 314, 1 June 1969, Pages 348–362, https://doi.org/10.2307/2230173 Published: 01 June 1969
Quick Stability Checks and Matrix Norms
Consider the difference equation system yt=b+Ayt-i; where yt is an nXl variable vector, b is an nXl constant vector and A is an nXn constant matrix. The fundamental necessary and sufficient stability condition for the system is /x(^)< 1, where [J.(A) is the modulus of the characteristic root of A of largest modulus. That is, IJ.(A) is the spectral radius of A, so-called because all roots of A lie on or within a circle of radius ix(A) in the compl…
Interactive markov chains
Markov chains, and various generalizations of them, almost universally assume that the transition probabilities applying to a single individual are independent of the behavior of other individuals in the population. That is, there is no interaction among individuals. This is an extremely limiting assumption in modelling social processes. This paper concerns interactive Markov chains, defined as Markov chains in which transition probabilities are …
A stability theorem for an interactive Markov chain
Eigenvalue immobility measures for Markov chains 1
Two eigenvalue measures of immobility are proposed for social processes described by a Markov chain. One is the second largest eigenvalue modulus of the chain's transition matrix. The other is the second largest eigenvalue modulus of a closely related transition matrix. The two eigenvalue measures are compared to each other and to correlation and regression‐to‐the‐mean measures. In illustrative applications to intergenerational occupational mobil…
Eigenvector Status Proxies in Markov Chain Mobility Models
In Markov chain studies of occupational mobility, an interesting empirical pattern has been reported. Certain transrtion matrix eigenvectors provide surprisingly accurate proxies for occupational status. Through a number of formal illustra tions, this paper suggests why the pattern might in theory be expected, in the occupational mobility context and in other mobility contexts
Monotone mobility matrices
The transition matrix of a discrete Markov chain is called monotone if each row stochastically dominates the row above it. Monotonicity is an ideal assumption to impose on a Markov chain model of mobility. Monotonicity is behaviorally weak yet mathematically strong. It is behaviorally weak in the sense that it is theoretically plausible and is empirically supported. It is mathematically strong in the sense that monotone Markov chains have a numbe…
Stability and monotonicity for interactive Markov chains
In a Markov chain model of a social process, interest often centers on the distribution of the population by state. One question, the stability question, is whether this distribution converges to an equilibrium value. For an ordinary Markov chain (a chain with constant transition probabilities), complete answers are available. For an interactive Markov chain (a chain which allows the transition probabilities governing each individual to depend on…
Imitation and the dynamics of norms
Dynamics of imitation
In the model, each person in a large population chooses between two options, such as adhering to or not adhering to a social norm. People observe each others’ choices at random and adjust their adherence probabilities in imitative directions. It is known from earlier work that, under strong restrictions on the imitation, the distribution of adherence probabilities will either evolve upward toward a high adherence equilibrium or downward toward a …
Actions influenced by a social network
A Note on Convergence of Adaptive Satisficing to Optimal Stopping
The model concerns a searcher making multiple searches from the same distribution of payoffs. The searcher does not know the distribution, does not attempt to infer it from cumulating information, and does not attempt to compute an optimal stopping rule. Instead the searcher follows thoroughly elementary adaptive rules. Nonetheless, the searcher converges to optimal stopping
Mathematics (11 works) · Economics (9 works) · Computer Science (8 works) · Markov chain (7 works) · Statistics (6 works) · Mathematical economics (5 works) · Artificial Intelligence (4 works) · Econometrics (4 works) · Game Theory and Applications (4 works) · Opinion Dynamics and Social Influence (4 works)