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multi-country-models-jedc-comparison-2011-

The folder “MMJ_JEDC_35_2011” contains MATLAB software for stochastic- simulation algorithm (SSA) and cluster-grid algorithm (CGA) accompanying the article "Solving the Multi-Country Real Business Cycle Model Using Ergodic Set Methods" by Serguei Maliar, Lilia Maliar and Kenneth L. Judd, (2011), Journal of Economic Dynamics and Control 35, 207-228.

multicountry_olg

multiplebubbles

:exclamation: This is a read-only mirror of the CRAN R package repository. MultipleBubbles — Test and Detection of Explosive Behaviors for Time Series

multiplier

replication material for “Understanding the Size of the Government Spending Multiplier: It’s All in the Sign”

multivariate-bayesian-predictive-synthesis-in-macroeconomic-forecasting

Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting, by Kenichiro McAlinn, Knut Are Aastveit, Jouchi Nakajima, Mike West

nar

The code for network autoregression model (NAR)

national-data

国家统计局的国家数据网站数据抓取器，可以直接使用1978-2016所有年鉴指标的csv数据

naturallimitswealthinequality

MATLAB code for the paper, "Natural Limits of Wealth Inequality and the Effectiveness of Tax Policy."

nci

Simulation code for "Words are the new numbers: A newsy coincident index of the business cycle"

nelson_siegel_svensson

Implementation of the Nelson-Siegel-Svensson interest rate curve model.

networks_hub

Home of code and output from the networks contagion project

neutralrate

Various models to derive the neutral interest rate

neverhpfilter

R package recreating econometric methods proposed in "Why You Should Never Use the Hodrick-Prescott Filter" by James Hamilton

nfda

Nonparametric Functional Data Analysis

nims

Forecasting NIMS

nkzlb

Programming code for "A Review of Solution and Estimation Methods for Nonlinear DSGE Models with the Zero Lower Bound"

nlma

nlma for Dynare

nn-zero-to-hero

Neural Networks: Zero to Hero

nolineartimeseriesanalysis

The codes in the toolbox can be used to perform nonlinear time series analysis on single(or multi) channel data. This is done by mapping the single channel data to phase space representation using Taken's embedding theorem (compute_psv.m). The parameters - optimal delay and dimension are estimated using first minimum of MI (compute_tau.m) and FNN method (compute_dim) respectively. The recurrence network can be constructed from the phase space vector using ComputeRecurrenceNetwork_ANN.m or ComputeRecurrenceNetwork_fixedRR.m. The topology of the RN can be further analysed using graph theoreticl quantifiers (you need BCT toolbox for this). One can also compute the complexity-entrropy plane using get_mpr_complexity.m for which the ordinal patterns are computed using get_ordinal_pattern_dist.m (see the function descp for more details). Also, the tool box contains python codes to generate variety of uni(or multi) variate surrogate data.

non-parametric-econometrics

This is the R code for several common non-parametric methods (kernel est., mean regression, quantile regression, boostraps) with both practical applications on data and simulations

nonlineartseries

Nonlinear time series analysis in R

nonparametric-functional-data-analysis

nonparametric-regression

methods to implement common nonparametric regression algorithms

novel-coronavirus-updates

新增确诊新型冠状病毒肺炎统计数据（每日更新）

nowcastdfm

DFM models in R

nowcasting

Nowcasting

nowcasting-1

R package for Dynamic Factor Models with mixed frequencies and unbalanced panel :chart_with_downwards_trend:

nprlab

NonParametric Regression Laboratory for MATLAB

nprmpi

Parallel nonparametric kernel smoothing methods for mixed data

npsdfd

Replication data and files for Christensen (2017): "Nonparametric Stochastic Discount Factor Decomposition"