search for: macroeconomics

Hi all, Please recommend good books for the following three categories. (I am aim at finance, macroeconomics, trading and business applications). (1) statistical (financial) data analysis; (2) time series; (3) econometrics. More specifically, I am looking for the following two types of books: (1) Books that provide big pictures and intuitions and books that connect dots... For example, there are lots...

Hello, Is there a package or sample code that shows how to do ex ante forecasts with a macroeconomic structural equations model? I looked at the "sem" package, which lets you estimate e.g. Klein's model, but I'm not sure how to make simulations using the full set of equations, including the identities. Thank you, Ronaldo Carpio rncarpio at yahoo.com

hello to all. I am working on macroeconomic data series of India, which in a yearly basis. I am unable to convert my data frame into time series. kindly help me. also using zoo and xts packages. but they take only monthly observations. 'data.frame': 30 obs. of 4 variables: $ year: int 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 ... $ cnsm: num 174 175 175 172 173 ... $ incm:

I'm an R newbie and had a question about the read.xls function. I've heard that this is often not a reliable function to use for importing data. However, I have created numerous xls files which contain information about voter turnout and macroeconomic indicators in India. I'm writing a paper on the relationship between economic growth and voter turnout. This is the command I use:

I am going to attend MSc Data Science in September, so I consider upgrading my system to be more efficient with my projects.I used RStudio for my Macroeconomics Undergraduate Thesis and I had a couple of loops which needed almost 30 minutes to occur. My system specifications are the following: - CPU: i7 4970k @ 4.0 GHz - RAM: 8GB DDR3 - Hard Drive: SSD M.2 950 PRO Since I have only used RStudio, is there any dramatic difference between R and...

Dear all, I am looking for a clustering method usefull to classify the countries in some clusters taking account of: a) the geographical distance (in km) between countries and b) of some macroeconomic indicators (gdp, life expectancy...). Are there some packages in R usefull for this? Thanks a lot for your help, Dorina

Hello, I am interested in looking at the dataset used by Stock and Watson in their "Macroeconomic Forecasting Using Diffusion Indexes (J. of Business and Econ. Statistics, April 2002, pp158-161) or the set used by D'Agostino and Giannone "Comparing Alternative Predictors [...]"(October 2006) in R. Does anyone know if the R-code to retrieve these series from FRED (as

> On 15 Sep 2017, at 11:38, yadav neog <yadavneog at gmail.com> wrote: > > hello to all. I am working on macroeconomic data series of India, which in > a yearly basis. I am unable to convert my data frame into time series. > kindly help me. > also using zoo and xts packages. but they take only monthly observations. > > 'data.frame': 30 obs. of 4 variables:

> On 15 Sep 2017, at 12:38, yadav neog <yadavneog at gmail.com> wrote: > > hello to all. I am working on macroeconomic data series of India, which in > a yearly basis. I am unable to convert my data frame into time series. Do you really need to convert your data to time series/xts/zoo? I don?t know you try what kind of an analysis but perhaps you don?t have to. > kindly

...on circular=F, the returned series don't have the correct dates. The removed dates are all at the beginning instead of half at the beginning and half at the end. It is particularly useful when we need to smooth the series (or remove a trend using a filter) before estimating a model (like in macroeconomics) or simply to plot the original series with the smoothed one. Of course, there is always the option of doing it by hand of the use circular=T and trim the series but I thought it would be nicer that way. Here is my suggestion (maybe not the nicest way to do it but it works) kernapply.ts <...

...in his "Bloom County" comic strip ) On Sun, Aug 20, 2017 at 7:39 AM, Vasilis Bardakos via R-help <r-help at r-project.org> wrote: > I am going to attend MSc Data Science in September, so I consider upgrading my system to be more efficient with my projects.I used RStudio for my Macroeconomics Undergraduate Thesis and I had a couple of loops which needed almost 30 minutes to occur. > My system specifications are the following: > > - CPU: i7 4970k @ 4.0 GHz > - RAM: 8GB DDR3 > - Hard Drive: SSD M.2 950 PRO > > Since I have only used RStudio, is there any dram...

tseries_0.3-0 at CRAN now contains the following new features: NelPlo Nelson-Plosser Macroeconomic Time Series garch Fit GARCH Models to Time Series get.hist.quote Download Historical Finance Data jarque.bera.test Jarque-Bera Test na.remove NA Handling Routines for Time Series garch contains a GARCH estimation routine together

tseries_0.3-0 at CRAN now contains the following new features: NelPlo Nelson-Plosser Macroeconomic Time Series garch Fit GARCH Models to Time Series get.hist.quote Download Historical Finance Data jarque.bera.test Jarque-Bera Test na.remove NA Handling Routines for Time Series garch contains a GARCH estimation routine together

> On 15 Sep 2017, at 11:38, yadav neog <yadavneog at gmail.com> wrote: > > hello to all. I am working on macroeconomic data series of India, which in > a yearly basis. I am unable to convert my data frame into time series. > kindly help me. > also using zoo and xts packages. but they take only monthly observations. > > 'data.frame': 30 obs. of 4 variables:

You can just use the same code that I provided before but now use your dataset. Like this df <- read.csv(file="data2.csv",header=TRUE) dates <- as.Date(paste(df$year,"-01-01",sep="")) myXts <- xts(df,order.by=dates) head(myXts) #The last command "head(myXts)" shows you the first few rows of the xts object year cnsm incm wlth

...lot(dat, xTickFreq="monthly", xTickSkip=6) # graph ends in 11/2008, but looks to start some time in late 1999 tisPlot(dat, xTickFreq="monthly", xTickSkip=12) # graph looks to end around 3/2009 ## end TIA, Kyle ___________________________________________ Research Associate, Macroeconomics Federal Reserve Bank of San Francisco [[alternative HTML version deleted]]

oky.. thank you very much to all of you On Sat, Sep 16, 2017 at 2:06 PM, Eric Berger <ericjberger at gmail.com> wrote: > You can just use the same code that I provided before but now use your > dataset. Like this > > df <- read.csv(file="data2.csv",header=TRUE) > dates <- as.Date(paste(df$year,"-01-01",sep="")) > myXts <-

Hi Frances, I have not touched the system.fit package for quite some time, but to solve your problem the following two pointers might be helpful: 1) Recast your model in the revised form, i.e., include your identity directly into your reaction functions, if possible. 2) For solving your model, you can employ the Gau?-Seidel method (see https://en.wikipedia.org/wiki/Gauss%E2%80%93Seidel_method).

Assuming the input data.frame, DF, is of the form shown reproducibly in the Note below, to convert the series to zoo or ts: library(zoo) # convert to zoo z <- read.zoo(DF) # convert to ts as.ts(z) # Note: DF <- structure(list(year = c(1980, 1981, 1982, 1983, 1984), cnsm = c(174, 175, 175, 172, 173), incm = c(53.4, 53.7, 53.5, 53.2, 53.3), with = c(60.3, 60.5, 60.2, 60.1, 60.7)),

Frances, I would not advise Gauss-Seidel for non linear models. Can be quite tricky, slow and diverge. You can write your model as a non linear system of equations and use one of the nonlinear solvers. See the section "Root Finding" in the task view NumericalMathematics suggesting three packages (BB, nleqslv and ktsolve). These package are certainly able to handle medium sized models.