Data: Scarcity of European Wife Material

[Down Low]

Here are some stats on European girls age 10-19. I picked ages 10 to 19 to give a good indication of wife material in the near future. The columns are country, number of girls age 10-19, their % of all females, and the number of males age 10-89 per girl age 10-19. These are all midyear 2012 population estimates. England is broken down by region. Notice that London has the worst ratio of men to wifeable women. For comparison, I began with comparable countries of the Anglo world. For the US, I used only white nonhispanics. US Census Dept. is the source of all except UK.

What I gather from all this is that for every new girl flowering, there are 5-10 guys constantly trying to fvck her.

Country . . . . . . .F(10-19) . . . . . . .% of all F . . . . . . .M(10-89)/F(10-19)
Europe . . . . . . .37,511,991 . . . . . . .9.788% . . . . . . .8.42

New Zealand . . . . . . .289,126 . . . . . . .13.300% . . . . . . .6.38
Australia . . . . . . .1,343,474 . . . . . . .12.235% . . . . . . .7.16
US white . . . . . . .11,209,090 . . . . . . .11.159% . . . . . . .7.68
Canada . . . . . . .1,938,696 . . . . . . .11.219% . . . . . . .7.80

BRITISH ISLES:

N. Ireland . . . . . . .119,642 . . . . . . .12.955% . . . . . . .6.39
Ireland . . . . . . .285,400 . . . . . . .12.073% . . . . . . .6.99
Wales . . . . . . .184,297 . . . . . . .11.820% . . . . . . .7.18
Jersey . . . . . . .5,629 . . . . . . .11.646% . . . . . . .7.32
W. Midlands . . . . . . .321,200 . . . . . . .11.412% . . . . . . .7.41
Scotland . . . . . . .305,000 . . . . . . .11.180% . . . . . . .7.45
South East . . . . . . .493,500 . . . . . . .11.267% . . . . . . .7.46
Yorkshire . . . . . . .302,800 . . . . . . .11.257% . . . . . . .7.55
North West . . . . . . .397,500 . . . . . . .11.146% . . . . . . .7.56
East . . . . . . . . . . .331,300 . . . . . . .11.104% . . . . . . .7.60
E. Midlands . . . . . . .257,200 . . . . . . .11.127% . . . . . . .7.71
South West . . . . . . .298,200 . . . . . . .11.027% . . . . . . .7.71
North East . . . . . . .144,300 . . . . . . .10.846% . . . . . . .7.76
Isle of Man . . . . . . .4,683 . . . . . . .10.926% . . . . . . .7.98
Guernsey . . . . . . .3,382 . . . . . . .10.250% . . . . . . .8.53
London . . . . . . .404,600 . . . . . . .9.880% . . . . . . .8.68

REST OF EUROPE:

Kosovo . . . . . . .159,827 . . . . . . .17.945% . . . . . . .4.87
Albania . . . . . . .263,153 . . . . . . .17.349% . . . . . . .4.90
Iceland . . . . . . .22,005 . . . . . . .14.039% . . . . . . .6.12
Gibraltar . . . . . . .2,044 . . . . . . .14.176% . . . . . . .6.15
Faroe Islands . . . . . . .3,542 . . . . . . .14.948% . . . . . . .6.27
Macedonia . . . . . . .137,058 . . . . . . .13.125% . . . . . . .6.65
Norway . . . . . . .301,796 . . . . . . .12.717% . . . . . . .6.80
Moldova . . . . . . .224,341 . . . . . . .11.912% . . . . . . .6.90
Denmark . . . . . . .348,533 . . . . . . .12.410% . . . . . . .6.91
Luxembourg . . . . . . .30,787 . . . . . . .11.907% . . . . . . .7.10
France . . . . . . .3,850,545 . . . . . . .11.483% . . . . . . .7.20
Netherlands . . . . . . .978,542 . . . . . . .11.575% . . . . . . .7.45
Finland . . . . . . .300,400 . . . . . . .11.180% . . . . . . .7.62
Liechtenstein . . . . . . .2,106 . . . . . . .11.366% . . . . . . .7.65
Croatia . . . . . . .247,608 . . . . . . .10.666% . . . . . . .7.80
San Marino . . . . . . .1,754 . . . . . . .10.595% . . . . . . .7.80
Malta . . . . . . .23,078 . . . . . . .11.209% . . . . . . .7.89
Bosnia . . . . . . .216,882 . . . . . . .10.905% . . . . . . .7.90
Belgium . . . . . . .573,342 . . . . . . .10.759% . . . . . . .7.92
Slovakia . . . . . . .296,219 . . . . . . .10.484% . . . . . . .7.96
Sweden . . . . . . .498,193 . . . . . . .10.851% . . . . . . .8.05
Hungary . . . . . . .521,495 . . . . . . .10.001% . . . . . . .8.10
Lithuania . . . . . . .183,893 . . . . . . .9.851% . . . . . . .8.12
Portugal . . . . . . .569,933 . . . . . . .10.312% . . . . . . .8.14
Montenegro . . . . . . .35,790 . . . . . . .10.848% . . . . . . .8.14
Serbia . . . . . . .388,083 . . . . . . .10.408% . . . . . . .8.18
Estonia . . . . . . .62,228 . . . . . . .8.968% . . . . . . .8.22
Poland . . . . . . .2,004,389 . . . . . . .10.113% . . . . . . .8.29
Switzerland . . . . . . .418,005 . . . . . . .10.392% . . . . . . .8.33
Belarus . . . . . . .475,901 . . . . . . .9.229% . . . . . . .8.35
Austria . . . . . . .433,112 . . . . . . .10.297% . . . . . . .8.37
Romania . . . . . . .1,113,803 . . . . . . .9.935% . . . . . . .8.56
Ukraine . . . . . . .2,143,203 . . . . . . .8.843% . . . . . . .8.60
Russia . . . . . . .6,501,753 . . . . . . .8.494% . . . . . . .8.87
Latvia . . . . . . .98,502 . . . . . . .8.375% . . . . . . .9.22
Italy . . . . . . .2,832,701 . . . . . . .8.936% . . . . . . .9.35
Bulgaria . . . . . . .321,310 . . . . . . .8.755% . . . . . . .9.40
Germany . . . . . . .3,850,573 . . . . . . .9.310% . . . . . . .9.41
Czech Rep . . . . . . .475,774 . . . . . . .9.123% . . . . . . .9.42
Greece . . . . . . .496,394 . . . . . . .9.024% . . . . . . .9.50
Spain . . . . . . .2,126,199 . . . . . . .8.924% . . . . . . .9.67
Slovenia . . . . . . .90,548 . . . . . . .8.840% . . . . . . .9.70
Andorra . . . . . . .3,980 . . . . . . .9.676% . . . . . . .9.85
Monaco . . . . . . .1,332 . . . . . . .8.514% . . . . . . .9.99

 

[Zarky]

Because there will be lots of 10 year olds going out with 89 year olds in the near future? These data make no sense to me. Or rather, why anyone would care about these data makes no sense to me.

You may wish to do another run where you look at the female cohort that interests you, and then look at the male cohort that the females would be statistically likely to choose.

I did that about a decade ago with the 2000 census data in southern california and came up with the following approximate numbers in my chosen demographics:

LA County 1.15 males for every 1 female
Orange County 1.2 males for every 1 female
SD County 1.32 males for every 1 female

The SD ratio is/was undoubtedly influenced by the military presence there.

These numbers were meaningful to me because I used white women in an age range I was interested in, and guessed at the types of men they would be looking for (same race, slightly older).

I'm simply not sure how yours is helpful to you or anyone else at this time.

 

[Who Dares Win]

I agree with zarky, the data is not relevant to our purpose.

It would be much better to compare the amount of 18-25 girls to the 25-35 guys (if your point is marriage), otherwise a simple female to male ratio in the age range 18-35.

Pointless to consider girls below 18 or guys above 35, while if you're gonna consider near future just remove x years from previous examples according to the time span you are interested in.

 

[Scaramouche]

Dear Down Low,
The statistical relevance(Meaning)...Seems a bit obscure to me..but take heart,you can only bonk one at a time...Or given the proclivities of some here three LOL.

 

[Down Low]

27-year-old men are in a 1-to-1 ratio with 17-year-old women. That's more or less true everywhere. 6% more males are born, but die of accidents at a higher rate. To say that residential areas have a nearly 1-to-1 ratio of young men to young women . . . is to say nothing.

Here's the point. If Zarky were looking for an old-fashioned young woman to marry -- a virgin -- what age range would Zarky be after? Well, puberty to about age 23, more or less.

If I were looking for an old-fashioned young woman to marry -- what age range would I be after? Puberty to about age 23, more or less.

If Scaramouche were looking, what age range would Scaramouche be after? Same.

Doesn't matter if you're 27, 37, 52, or 68. The biology of female fertility is not affected by the age of the male. All men should be going after the youngest, most fertile, and least damaged women. It's just plain disgusting that some men kowtow to femcvnt shaming and c0ckblock themselves out of pursuing women significantly younger than themselves.

I chose the 10-to-19 groups instead of 15-to-24 to (1) reflect the sharp decline in births that will affect the availability of marriageable girls very soon, and (2) to include current 14-year-olds but exclude 24-year-olds. The typical age of a first birth in developed countries has been 23 for some years.

The data is rife with conclusions. Some men rave about Eastern Europe. Except for the shining example of Moldova, the Russian-speaking countries have some of the worst ratios of men to marriageable women. German-speaking countries are also below average. French-speaking countries are about the same as the British Isles -- and the Irish island is much the best. Scandinavia is the best single group, but Sweden disappoints. The shocker is that Spain, Italy, and Greece are so overloaded with men compared to blossoming girls.

Anyone could do the same analysis of Africa, Asia, or Latin America -- whichever women you desire. It's better than just accepting broad generalizations at face value about girls in Catholic countries, or what have you. We have computers at our fingertips. Why not use them to compute?

 

[taiyuu_otoko]

Doesn't matter if you're 27, 37, 52, or 68. The biology of female fertility is not affected by the age of the male. All men should be going after the youngest, most fertile, and least damaged women. It's just plain disgusting that some men kowtow to femcvnt shaming and c0ckblock themselves out of pursuing women significantly younger than themselves.

Emphasis mine.

Concur one hundred percent.

So does my DNA.

 

[Maeisgood]

Read Death of the West by Patrick Buchanan.

 

[MatureDJ]

I think I'm moving to Kosovo ...

 

[synergy1]

Your modeling is fairly flawed IMO. The assumptions need some work so you can present the actual data a bit better. For example, One is looking at only one demographic without considering that the other demographic (18+) is already integrated into the match schema. In other words, the men ages 20-50, say, will be largely tied up with the women aged 18+. Further, you need to add a weight factor as not all 5 men will have equal chances with the women. In all reality, it will be one of those 5 men who will have most of the luck while the others probably will see marked drop in their success. Another factor one could possibly implement is the ovulation cycle which adds an element of "chance" into the mix. For example, if there are 2 days out of a 30 day period where women are more prone to sex, courtship etc, this means one mans chance will yield different outcomes approximately 1 out of 15 times. (assuming one attempt occurs on one day)

In other words, to adequately prove scarcity, one would need to really get into the nuts and bolts. Personally, I don't have the interest and feel that its much easier to simply be the one out of 5 guys who women would rather get with.

 

[Zarky]

All men should be going after the youngest, most fertile, and least damaged women.

Well that's great, but not all men do, and the vast, vast majority of men have no -- and I mean no -- chance of obtaining those women. It's a zero-sum game, and no matter how much "game" you have there are plenty of women you will never have a chance with.

Despite how awesome you think you are, there are millions of guys out there who are richer, better looking, taller, smarter, funnier, and who have more game than you. And even only a small fraction of them will ever have what it takes to get the most desirable women.

Let's face it, if you're 70-80 years old, 99.9999% of women in their teens and twenties want absolutely nothing to do with you even if you're filthy rich. So you are, in effect, non-existent to them sexually, no matter how hard you're trying. So those data should be pulled out, for starters.

Some men rave about Eastern Europe.

Those men are idiots. I've dated my share of eastern european broads and every single one is 1) attractive and well kept and 2) a ridiculous gold-digger. I've dated 3 russians and 1 polish chick and would never date another for any reason. They're absolutely mercenary (although in fairness, when they're into you, which can take years, they are extremely loyal and would probably take a bullet for you).

EDIT:

Ok, after reading the OP again and thinking about it, I think I understand what he's getting at. It's sort of a big-picture approach. Comparing, basically, the ratio of young women to all men. I think it's interesting only insofar as how the countries compare with each other, not in the absolute figures. You could do away with the numbers completely and simply have a list of countries where, as a man, you're surrounded by the most young women. I suppose if you were looking to travel and settle down in a place it could be of interest, but I still think a more useful chart would be one where you compare your own demographic with that of women you're interested in and have a reasonable shot with.

For example, I'd compare the ratios of mid-30s white men to, say, mid-20s white women. That would be of interest to me. Not the 17 year olds because my odds of obtaining them are vanishingly small. And I would discount the eastern european countries out of hand because even if their ratios were fantastic, the women there are awful.

The OP reminds me of those articles which state, "The Top 10 Cities with The Most Beautiful People" or "Top 10 Places to Retire." They're kind of interesting, but are they really helpful for any particular person?

I do appreciate the number crunching though. I remember, years ago, I'm talking 1999 or something, I posted something on ASF showing that, if you're a man who is considered an "8" or above looks-wise, you would have more luck getting laid if you went from woman to woman rather than focusing on one particular woman. And if you were 6 or below, that was reversed. Wish I could find that spreadsheet

 

[Down Low]

In another thread, I suggested some countries have better wife potential than China. Here's a strict comparison with the above data:

Country . . . . . . .F(10-19) . . . . . . .% of all F . . . . . . .M(10-89)/F(10-19)
Philippines . . . . . .10,568,392 . . . . . . .20.397% . . . . . . .3.74
Venezuela . . . . . . . 2,717,990 . . . . . . .19.164% . . . . . . .4.08
Colombia . . . . . . . .4,060,608 . . . . . . .17.740% . . . . . . .4.52

...all of which are better than anywhere in Europe. The country I argued against has a sex ratio more like Europe:

China . . . . . . . . .82,678,122 . . . . . . .12.693% . . . . . . .7.37

Your modeling is fairly flawed IMO. The assumptions need some work so you can present the actual data a bit better. For example, One is looking at only one demographic without considering that the other demographic (18+) is already integrated into the match schema. In other words, the men ages 20-50, say, will be largely tied up with the women aged 18+. Further, you need to add a weight factor as not all 5 men will have equal chances with the women. In all reality, it will be one of those 5 men who will have most of the luck while the others probably will see marked drop in their success. Another factor one could possibly implement is the ovulation cycle which adds an element of "chance" into the mix. For example, if there are 2 days out of a 30 day period where women are more prone to sex, courtship etc, this means one mans chance will yield different outcomes approximately 1 out of 15 times. (assuming one attempt occurs on one day)

In other words, to adequately prove scarcity, one would need to really get into the nuts and bolts. Personally, I don't have the interest and feel that its much easier to simply be the one out of 5 guys who women would rather get with.

Perhaps it's just the other way around. In Europe, it could be that women are totally wh0red out and want sugar daddies above all else. In such a divorce / never-married / open-relationships environment, do men really stop flirting when they're in temporary "long-term" relationships?

Those men are idiots. I've dated my share of eastern european broads and every single one is 1) attractive and well kept and 2) a ridiculous gold-digger. I've dated 3 russians and 1 polish chick and would never date another for any reason. They're absolutely mercenary (although in fairness, when they're into you, which can take years, they are extremely loyal and would probably take a bullet for you).

Agree they 100% worship money. Even the ugly ones think they're attractive if they put on big sunglasses with evening dark lipstick, and an overstyled leather jacket with open-toed sandles. Loud, obnoxious, no sense of style, just worthless cvnts.

And I would discount the eastern european countries out of hand because even if their ratios were fantastic, the women there are awful.

I'm saying that the women are awful, in part, because the ratios are so awful. There are too many men chasing too few women.

It would be much better to compare the amount of 18-25 girls to the 25-35 guys (if your point is marriage)...

My pleasure.

Country . . . . . . .F(18-25) . . . . . . .% of all F . . . . . . .M(25-35)/F(18-25)
Europe . . . . . . .36,936,383 . . . . . . .9.638% . . . . . . .1.58

Albania . . . . . . .234,004 . . . . . . .15.427% . . . . . . .0.98
Faroe Islands . . . . . .2,923 . . . . . . .12.336% . . . . . . .1.13
Jersey . . . . . . .5,983 . . . . . . .12.378% . . . . . . .1.19
Sweden . . . . . . .494,766 . . . . . . .10.776% . . . . . . .1.25
Denmark . . . . . . .272,802 . . . . . . .9.714% . . . . . . .1.27
Norway . . . . . . .243,886 . . . . . . .10.277% . . . . . . .1.28
Isle of Man . . . . . . .3,961 . . . . . . .9.241% . . . . . . .1.29
Kosovo . . . . . . .137,183 . . . . . . .15.402% . . . . . . .1.30
Iceland . . . . . . .18,288 . . . . . . .11.668% . . . . . . .1.32
Monaco . . . . . . .1,082 . . . . . . .6.916% . . . . . . .1.32
Gibraltar . . . . . . .1,898 . . . . . . .13.163% . . . . . . .1.32
Netherlands . . . . . . .816,289 . . . . . . .9.655% . . . . . . .1.37
Moldova . . . . . . .243,730 . . . . . . .12.941% . . . . . . .1.37
United Kingdom . . . . . .3,356,771 . . . . . . .10.577% . . . . . . .1.38
Estonia . . . . . . .70,037 . . . . . . .10.093% . . . . . . .1.40
Guernsey . . . . . . .3,336 . . . . . . .10.111% . . . . . . .1.41
Austria . . . . . . .391,194 . . . . . . .9.300% . . . . . . .1.43
Lithuania . . . . . . .204,390 . . . . . . .10.949% . . . . . . .1.43
Latvia . . . . . . .126,952 . . . . . . .10.794% . . . . . . .1.43
Finland . . . . . . .255,335 . . . . . . .9.502% . . . . . . .1.45
Belgium . . . . . . .495,442 . . . . . . .9.297% . . . . . . .1.45
France . . . . . . .3,106,352 . . . . . . .9.263% . . . . . . .1.45
Luxembourg . . . . . . .25,287 . . . . . . .9.780% . . . . . . .1.46
Germany . . . . . . .3,660,460 . . . . . . .8.851% . . . . . . .1.48
San Marino . . . . . . .1,274 . . . . . . .7.696% . . . . . . .1.51
Liechtenstein . . . . . .1,709 . . . . . . .9.223% . . . . . . .1.52
Bosnia . . . . . . .207,154 . . . . . . .10.415% . . . . . . .1.53
Macedonia . . . . . . .118,543 . . . . . . .11.352% . . . . . . .1.53
Malta . . . . . . .21,588 . . . . . . .10.485% . . . . . . .1.53
Belarus . . . . . . .549,344 . . . . . . .10.654% . . . . . . .1.57
Switzerland . . . . . . .375,782 . . . . . . .9.342% . . . . . . .1.57
Ukraine . . . . . . .2,482,093 . . . . . . .10.242% . . . . . . .1.58
Croatia . . . . . . .215,385 . . . . . . .9.278% . . . . . . .1.60
Serbia . . . . . . .351,130 . . . . . . .9.417% . . . . . . .1.61
Russia . . . . . . .7,964,223 . . . . . . .10.405% . . . . . . .1.61
Hungary . . . . . . .484,453 . . . . . . .9.290% . . . . . . .1.62
Italy . . . . . . .2,512,944 . . . . . . .7.927% . . . . . . .1.63
Slovakia . . . . . . .301,484 . . . . . . .10.671% . . . . . . .1.67
Romania . . . . . . .1,156,159 . . . . . . .10.313% . . . . . . .1.70
Czech Rep . . . . . . .492,412 . . . . . . .9.442% . . . . . . .1.72
Bulgaria . . . . . . .331,971 . . . . . . .9.045% . . . . . . .1.73
Poland . . . . . . .2,054,307 . . . . . . .10.365% . . . . . . .1.74
Portugal . . . . . . .479,068 . . . . . . .8.668% . . . . . . .1.79
Ireland . . . . . . .233,734 . . . . . . .9.887% . . . . . . .1.82
Slovenia . . . . . . .88,775 . . . . . . .8.667% . . . . . . .1.83
Greece . . . . . . .435,886 . . . . . . .7.924% . . . . . . .1.88
Montenegro . . . . . . .34,278 . . . . . . .10.390% . . . . . . .2.03
Spain . . . . . . .1,867,328 . . . . . . .7.838% . . . . . . .2.10
Andorra . . . . . . .3,008 . . . . . . .7.313% . . . . . . .2.19

The numbers are pretty much the same. The decline in births impacts the Republic of Ireland far more, and the German- and Russian-speaking countries far less. Your demographics are more for dating purposes than for explaining a possible reason for some countries producing b1tchier women.

 

[Down Low]

...I still think a more useful chart would be one where you compare your own demographic with that of women you're interested in and have a reasonable shot with.

For example, I'd compare the ratios of mid-30s white men to, say, mid-20s white women. That would be of interest to me. Not the 17 year olds because my odds of obtaining them are vanishingly small.

Country . . . . . . .F(23-27) . . . . . . .% of all F . . . . . . .M(33-37)/F(23-27)
Europe . . . . . . .25,487,123 . . . . . . .6.650% . . . . . . .1.04

Jersey . . . . . . .4,056 . . . . . . .8.392% . . . . . . .0.56
Albania . . . . . . .139,204 . . . . . . .9.177% . . . . . . .0.58
Kosovo . . . . . . .88,314 . . . . . . .9.915% . . . . . . .0.75
Moldova . . . . . . .166,232 . . . . . . .8.827% . . . . . . .0.81
Estonia . . . . . . .49,943 . . . . . . .7.197% . . . . . . .0.82
Latvia . . . . . . .91,107 . . . . . . .7.747% . . . . . . .0.82
Russia . . . . . . .6,154,097 . . . . . . .8.040% . . . . . . .0.86
Belarus . . . . . . .398,734 . . . . . . .7.733% . . . . . . .0.89
Ukraine . . . . . . .1,813,126 . . . . . . .7.481% . . . . . . .0.89
Lithuania . . . . . . .137,616 . . . . . . .7.372% . . . . . . .0.90
United Kingdom . . . . . . .2,154,206 . . . . . . .6.788% . . . . . . .0.91
Sweden . . . . . . .297,603 . . . . . . .6.482% . . . . . . .0.93
Germany . . . . . . .2,431,783 . . . . . . .5.880% . . . . . . .0.97
Gibraltar . . . . . . .1,118 . . . . . . .7.754% . . . . . . .0.98
Guernsey . . . . . . .2,120 . . . . . . .6.425% . . . . . . .0.98
Netherlands . . . . . . .512,081 . . . . . . .6.057% . . . . . . .0.98
Iceland . . . . . . .10,691 . . . . . . .6.821% . . . . . . .1.00
Bosnia . . . . . . .141,529 . . . . . . .7.116% . . . . . . .1.01
Austria . . . . . . .246,896 . . . . . . .5.870% . . . . . . .1.01
Isle of Man . . . . . . .2,350 . . . . . . .5.483% . . . . . . .1.02
France . . . . . . .1,969,383 . . . . . . .5.873% . . . . . . .1.03
Norway . . . . . . .142,692 . . . . . . .6.013% . . . . . . .1.03
Macedonia . . . . . . .77,920 . . . . . . .7.462% . . . . . . .1.04
Faroe Islands . . . . . .1,477 . . . . . . .6.233% . . . . . . .1.07
Luxembourg . . . . . . .16,048 . . . . . . .6.206% . . . . . . .1.07
Belgium . . . . . . .305,514 . . . . . . .5.733% . . . . . . .1.08
Poland . . . . . . .1,446,279 . . . . . . .7.297% . . . . . . .1.08
Finland . . . . . . .154,656 . . . . . . .5.756% . . . . . . .1.09
Croatia . . . . . . .143,179 . . . . . . .6.168% . . . . . . .1.09
Switzerland . . . . . . .250,121 . . . . . . .6.218% . . . . . . .1.10
Liechtenstein . . . . . .1,074 . . . . . . .5.796% . . . . . . .1.10
Malta . . . . . . .13,674 . . . . . . .6.642% . . . . . . .1.11
Denmark . . . . . . .159,277 . . . . . . .5.671% . . . . . . .1.11
Serbia . . . . . . .234,960 . . . . . . .6.302% . . . . . . .1.12
Monaco . . . . . . .618 . . . . . . .3.950% . . . . . . .1.17
Slovakia . . . . . . .204,473 . . . . . . .7.237% . . . . . . .1.17
Romania . . . . . . .841,526 . . . . . . .7.506% . . . . . . .1.18
Bulgaria . . . . . . .234,398 . . . . . . .6.387% . . . . . . .1.19
Ireland . . . . . . .165,554 . . . . . . .7.003% . . . . . . .1.21
Slovenia . . . . . . .62,918 . . . . . . .6.143% . . . . . . .1.25
San Marino . . . . . . .799 . . . . . . .4.826% . . . . . . .1.28
Montenegro . . . . . . .24,024 . . . . . . .7.282% . . . . . . .1.32
Italy . . . . . . .1,655,693 . . . . . . .5.223% . . . . . . .1.33
Greece . . . . . . .305,742 . . . . . . .5.558% . . . . . . .1.35
Portugal . . . . . . .312,702 . . . . . . .5.658% . . . . . . .1.40
Hungary . . . . . . .305,810 . . . . . . .5.865% . . . . . . .1.43
Czech Rep . . . . . . .322,920 . . . . . . .6.192% . . . . . . .1.43
Spain . . . . . . .1,288,915 . . . . . . .5.410% . . . . . . .1.66
Andorra . . . . . . .1,971 . . . . . . .4.792% . . . . . . .2.02

 

[Zarky]

LOL thanks! I'll be planning my trip to Jersey shortly.