I use Stata SE/14.

My survey and subsequent data set (n=2,682) contains five string variables that include four "check all that apply" response options. For example, "In the last month, which of the following behaviors have you witnessed by community members in your neighborhood?" Respondents could select one, or up to all responses. Because we didn't include a "don't know" option in the original survey, such responses were added in later, by hand, during data entry in excel. These variables were all stored as string. This means I have variables that look, for example, like this:

VAR X Freq.

1 | 523

1,2 | 34

1,2,3 | 10

1,2,3,4 | 3

1,2,4 | 2

1,3 | 44

1,3,4 | 32

Don't know| 8

Not sure | 6

N/A | 3

No answer | 2

Because of the fact that the responses are both numeric and nonnumeric, and contain multiple values per cell, I am not sure where to start in terms of recoding such variables. I have tried the following commands:

But received the response VARX contains nonnumeric characters; no generate

I then tried

and obtained the response:

type mismatch

r(109);

Is there another way to do this?

Thank you in advance for your assistance,

Florence

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1) performing a goodness of fit test

2) correcting for overdispersion.

Any suggestions would be highly appreciated,

Regards,

Sonia Menon]]>

Could you help me to resolve this problem?

A subject X takes 5 distinct decisions over 5 periods.

The utility function of the subject X is represented by a function type

U (β) = constant or U (α) according to the periods. α and β represent social preference parameters (table 1)

My objective is to measure the weight of the parameters α and β on all 5 observations of the subject.

Which econometric test with notions of optimization (optimum parameters β and α) can be considered in this case?

Round 1 | U= 13-1,8β |

Round 2 | 14-1,2β |

Round 3 | 0,6α+14 |

Round 4 | 0,2α-15,33 |

Round 5 | 15,66-0,8β |

I have a dataset that looks like this where data from redcap is imported into separate forms and then the variables for each form are listed horizontally. I am struggling with the reshape command because the data is both long and wide at the same time.

I would like to have a single row per study id number with all the data in wide form.

This is what the data currently looks like.

studyID | form | form_a_var_1 | form_a_var_2 | form_a_var_3 | form_b_var_1 | form_b_var_2 | form_b_var_3 |

1 | a | x | x | x | |||

1 | b | x | x | x | |||

2 | a | x | x | x | |||

2 | b | x | x | x |

studyID | form | form_a_var_1 | form_a_var_2 | form_a_var_3 | form_b_var_1 | form_b_var_2 | form_b_var_3 |

1 | a | x | x | x | x | x | x |

2 | a | x | x | x | x | x | x |

Ribka]]>

I have decided to use a multinomial logit model in order to predict foreign exchange crises. As a dependent variable i have constructed a market pressure index which is influenced by the following variables : real exchange rate (RER), the ratio of money supply (M3) to reserves (M3R), the growth rate of exports (ΔX) and imports (ΔM) and the growth rate of industrial production index (ΔIP). (All data is for Denmark)

The model is similar as the one used by Ghazi Al-Assaf in his papaer of 2017 (which I have attached ).

The question is how to use the multinomial logit model in order to see the impact of the independent variables onto the dependent one (Market Pressure) into the future time. As i know the multinomial logit model sets two outcomes with different probabilities: when Market pressure average plus its standard deviation exceeds Market pressure value than the crisis will happen.

I would be glad and i would appreciate if you could provide me with some help how to implement an multinomial logistic regression model in STATA.

Best regards to everyone!!]]>

I Have a strongly balanced short panel (t=3) data and over 3000 observations in each panel. I am trying to run a village level fixed effects instead of a household fixed effect (I want the mean deviation transformation of the variables to be based on village means not household means but I also want to control for the household fixed effects). Here is my syntax:

HTML Code:

reghdfe y1 x1 [pweight=pw], a(village household) cluster(village)

Am I doing it right? I cannot help it but think that I am not.

I am also interested in the between villages effects estimation. I have mean collapsed my data by village and run OLS. Is there a built-in way of accessing the between effects for -reghdfe-?

Any help is much appreciated.

Yonatan

]]>Yonatan