shortage_analysis {markets}

Analysis of shortages

Description

The following methods offer functionality for analyzing estimated shortages of the market models. The methods can be called either using directly a fitted model object, or by separately providing a model object and a parameter vector.

Usage

shortages(fit, model, parameters)

normalized_shortages(fit, model, parameters)

relative_shortages(fit, model, parameters)

shortage_probabilities(fit, model, parameters)

shortage_indicators(fit, model, parameters)

shortage_standard_deviation(fit, model, parameters)

## S4 method for signature 'missing,market_model,ANY'
shortages(model, parameters)

## S4 method for signature 'missing,market_model,ANY'
normalized_shortages(model, parameters)

## S4 method for signature 'missing,market_model,ANY'
relative_shortages(model, parameters)

## S4 method for signature 'missing,market_model,ANY'
shortage_probabilities(model, parameters)

## S4 method for signature 'missing,market_model,ANY'
shortage_indicators(model, parameters)

## S4 method for signature 'missing,market_model,ANY'
shortage_standard_deviation(model, parameters)

## S4 method for signature 'missing,diseq_stochastic_adjustment,ANY'
shortage_standard_deviation(model, parameters)

## S4 method for signature 'market_fit,missing,missing'
shortages(fit)

## S4 method for signature 'market_fit,missing,missing'
normalized_shortages(fit)

## S4 method for signature 'market_fit,missing,missing'
relative_shortages(fit)

## S4 method for signature 'market_fit,missing,missing'
shortage_probabilities(fit)

## S4 method for signature 'market_fit,missing,missing'
shortage_indicators(fit)

## S4 method for signature 'market_fit,missing,missing'
shortage_standard_deviation(fit)

Arguments

fit

A fitted model object.

model

A market model object.

parameters

A vector of parameters at which the shortages are evaluated.

Details

shortages

Returns the predicted shortages at a given point.

normalized_shortages

Returns the shortages normalized by the variance of the difference of the shocks at a given point.

relative_shortages

Returns the shortages normalized by the supplied quantity at a given point.

shortage_probabilities

Returns the shortage probabilities, i.e. the probabilities of an observation coming from an excess demand state, at the given point.

shortage_indicators

Returns a vector of indicators (Boolean values) for each observation. An element of the vector is TRUE for observations at which the estimated shortages are non-negative, i.e. the market at in an excess demand state. The remaining elements are FALSE. The evaluation of the shortages is performed using the passed parameter vector.

shortage_standard_deviation

Returns the standard deviation of excess demand.

Value

A vector with the (estimated) shortages.

Functions

• shortages(): Shortages.

• normalized_shortages(): Normalized shortages.

• relative_shortages(): Relative shortages.

• shortage_probabilities(): Shortage probabilities.

• shortage_indicators(): Shortage indicators.

• shortage_standard_deviation(): Shortage standard deviation.

Examples

# estimate a model using the houses dataset
fit <- diseq_deterministic_adjustment(
  HS | RM | ID | TREND ~
    RM + TREND + W + CSHS + L1RM + L2RM + MONTH |
      RM + TREND + W + L1RM + MA6DSF + MA3DHF + MONTH,
  fair_houses(),
  correlated_shocks = FALSE,
  estimation_options = list(control = list(maxit = 1e+5))
)

# get estimated normalized shortages
head(normalized_shortages(fit))

# get estimated relative shortages
head(relative_shortages(fit))

# get the estimated shortage probabilities
head(shortage_probabilities(fit))

# get the estimated shortage indicators
head(shortage_indicators(fit))

# get the estimated shortages
head(shortages(fit))

# get the estimated shortage standard deviation
shortage_standard_deviation(fit)